Holarchy

Work in Progress: This article is still in the developmental stage. Please do not base any work on this content, any aspect of it may undergo change or be removed at any time without notice.

A holarchy is a hierarchical structure in which each part or component forms an autonomous whole that is also a part of a larger system. This concept was introduced by the American philosopher Arthur Koestler, who argued that complex systems could be understood as interconnected networks of holons – self-organising units that are both parts and wholes at the same time. In other words, a holarchy is a structure in which each part has its own identity and purpose while simultaneously being part of a larger whole. Koestler called these two aspects of a holon the self-assertive and the integrative behaviours respectively. He described the former as an inward-facing system operating with flexible strategies within an individual holon. The latter as an outward-facing system operating with fixed rules as a network, or holarchy.

In terms of information technology, we might classify the holarchy concept as a universal middleware and as a "web3" concept in both the decentralised and semantic senses.

About this document

This document (as of March 2024) is still in draft form, it is not yet complete in the sense of a buildable specification, but gives a clear idea of what we're trying to achieve.

Intended audience

This document is primarily for reasonably IT-savvy people with an interest in independence, sovereignty and decentralised offline-first organisation. This means people who are already familiar with the pitfalls of centralised management and control.

Document purpose

The primary motivation for writing this is for our own internal group to have a clear picture of the current state of the concept and high-level overview of the project. The concept is still being developed and refined, and there's so many aspects to it, and we need to have a clear summary of how they all tie together and contribute to the idea as a whole.

We want to introduce what the holarchy project is and how people might benefit from using the system, once operational. Also to clarify what the holarchy is as a definite system.

The intention is that every concept discussed below contributes a specific small piece to the larger holarchy concept, never appearing as isolated fragments that are difficult to integrate with the main conceptual thread.

References

For now we're using the numbered references mainly for interesting side notes and reminders rather than sources and citations

Use of AI

I haven't found the current elementary LLM technology to be very useful for direct copying and pasting of content, perhaps because the concept herein is very novel. Consequently, very little content in this document has been written by AI. One exception is that some of the generic introductions to concepts such as the first paragraph of the Three abstraction layers section.

Where I've found AI extremely useful is as a conversational partner to bounce ideas around, and help with research and refining concepts. For example, with AI you can search for existing concepts by similarity to others or extract the common conceptual aspects from different fields. You can search for, summarise and extract specific concepts from large bodies of work, or you can merge, extend, filter or generalise concepts. We've never had this sort of flexibility before, and that's a real game-changer, and with AGI just around the corner, this aspect of AI is set to explode exponentially.

Etymology of "holarchy"

The suffix "-archy" comes from the Greek "archein," meaning "to rule" or "to lead". Based on its etymology, "holarchy" implies a form of organisation or structure where each unit (or 'whole') is both a part and a whole in itself. It suggests a hierarchical system where each level or unit is a self-contained whole that fits into larger wholes. This concept often appears in systems theory and organisational studies, emphasising the nested, self-similar, or fractal nature of systems.

Another closely related word is "holocracy". Both concepts involve a recognition of "wholeness" in each part of a system. Holarchy integrates this with a hierarchical structure, offering a balance between rules and autonomy, whereas holocracy is more inclined towards ensuring autonomy and distributed governance.

The term "holarchy" better describes our system, because it's explicitly defining a hierarchical system of authoritative rules - collaborative rules that provably maximise individual autonomy. "Holocracy" best fits a purely decentralised system that does not define any concept of authority or hierarchy.

Organic technology

Many people who are strong believers in the idea of humans living fully in accord with nature think that technology has no place in this vision. But by looking at how the cells in the human body are able to live together as a community with a population of over fifty trillion reveals that technology is essential. The cells manufacture and maintain huge infrastructures including the equivalent of buildings that are tens of thousands of stories high, sophisticated networking systems and even an energy based financial and banking system.

The fractal nature of life allows us to equate the biological cell with a person, and a single person with the planetary organism. In his book Spontaneous Evolution, Bruce Lipton shows us that we can learn from our cells how to live together in peace and harmony as a single organism since they're a living example of it, and have been doing it for millions of years.

The rules that define fractals are deceptively simple. Often a few lines of code can yield a mathematical structure of incredible harmony and beauty such as the example shown in the image to the right.

Holarchy is a complex fractal due to being a recursive structure of feedback relationships. It offers us a framework that can achieve the kind of large-scale organisation we see in biology, and can be understood clearly in terms of our own technological infrastructure.

Evolution and economy

Both evolution and economy are systems which, like fractals, involve extreme complexity and yet can be defined in very simple terms. This is quite well known in the case of evolution, for example David Deutsch described it in his book The Beginning of Infinity as being simply the "creation of knowledge through alternating variation and selection".

This complexity from simplicity aspect is not so well known in the case of economy, where in our modern society, we've generally come to believe that only extremely complex mathematical tools can be used to manage something as complex and nuanced as the economy.

A more traditional perspective however, is the so-called "Austrian school" of economics which is strongly opposed to the idea of a centrally planned or regulated economy. The core Austrian idea is that economic order emerges naturally and efficiently from the interactions of individual agents, each pursuing their own interests within a free market. Any deviation from this reduces the efficiency of the economy and reduces the sovereignty and wealth of the agents.

The reason for introducing evolution and economy here is because holarchy is an organisational pattern which inherently embodies these two systems, both complimenting and augmenting each other. The evolutionary system underlies the specialisation of the economy, but yet also depends on the economy the distribution of material resource.

Although holarchy is not traditionally connected with these two behaviours in such a direct way, when it's defined in terms of the specific four-quadrant mechanism we're introducing herein, two feedback loops emerge which inherently express them.

The role of internet

The internet connects all of Humanity, and is evolving into an ever more complex, resilient and organised system. It's organised in layers of open protocols from the most fundamental physical layer up to the high-level organised layer of application protocols.

The internet is generally referred to as having gone through a few different versions or phases, the first was characterised by servers and technology specialists being responsible for generating and maintaining the content. The name "web 2.0" was given to the broad phase that came with blog and wiki software in which the vast majority of content was being generated by the end users.

The meaning of "web3" was originally used to refer to the semantic web which was envisioned to be a new level of organisation of the web's content brought about by metadata annotations. But web3 started to slow in its progress with corporate interests gravitating instead towards deep learning and AI as solutions to organisation. The "web3" term ended up referring to the decentralised nature of the web which started gaining popularity with the introduction of blockchain technology.

Interestingly, the holarchy architecture actually fulfils both definitions of "web3", because it maintains an evolving ontology in which all content is organised semantically, as well as being able to function ideally in a fully decentralised environment. It's a unified ontology of knowledge as well as a map of the usage of that knowledge.

Knowledge-sharing and organisation are so essential to a harmonious society, that they ought to be provided at the basic abstraction layer of the common networking protocols. The holarchy is a networking protocol that allows participants of the network (holons) to interact together with a common means of organising attention and resources and of sharing, adapting, using and assessing knowledge..

Universal middleware

The concept of a universal middleware, or as Elon Musk referred to the concept, the "everything app", is an inevitable phase of the way we organise using information technology. Essentially, China has already arrived at this "everything app" phase with WeChat which many call the "operating system of china".

Soon all apps across all technologies and platforms will be fully usable by API (most already are) so that AI can use them on our behalf. Application interfaces aimed at desktop, web and even mobile contexts will eventually fall into decline through lack of demand.

There will be many universal middleware offerings, most likely every large tech player will be pushing their own versions, but also libre software will have its offerings too, and these will typically be designed to be maximally interoperable with each other.

It's important to note that while there are many different universal middleware projects, and potentially even many of them that are modelled directly on the holarchy principle, there can be only one holarchy.

This is not to say that all of them are fake except for the one true holarchy, it's just that one of the main objectives of the holarchy concept itself is unification. So all holarchy deployments, no matter their origins, are objectively dedicated to seeking each other out, and merging into a single network.

Self-organisation

Self-organisation is a concept usually associated with self-organising systems. These are systems that organise themselves spontaneously without the need for external input. Holons are self-organising, which means they involve a structure or pattern that emerges without any external command or central control directing its formation.

The concept of cognitive agency or cognition (in a very generalised form) plays a central role in the functioning of self-organising systems. Agency, in this context, does not refer only to human-like thought processes or consciousness but to a system's ability to process information, respond to environmental stimuli, and adapt accordingly. This form of "perception" enables the system to modify its behaviour based on the state it detects, leading to dynamic adjustments that enhance its stability or efficiency.

This subjective agency aspect of the system means that often the best analogies to concepts in the holon model are things that we're very familiar with in our own everyday experience. For example we say that a holon's "salience is that which is within its field of awareness" or we might refer to a holon's "thread if experience" or that a holon's "unconscious" activity is that which does not receive focus from high-level agency. All these things have obvious and precise meanings in the context of the holon model.

We can say that the self-organisation concept gains a sense of self by the inclusion of this cognitive aspect, thereby becoming a self-organisation, a self-instantiating class.

This is the state of self as an organisation. A holon is a structure of state and behaviour that self-organises and co-evolves with its environment. The concept of self-organisation is essentially also stating that self is an organisation (i.e. a group of entities that are organised toward a common objective) and that it has subjective agency.

The concept of self-organisation implies a direction of self-sovereignty, full unencumbered agency over and responsibility for ones body, actions, decisions and time. This agency over ourselves is our responsibility to maintain, both for ourselves and in supporting the collective responsibility for it too.

The concept of private property is defined as the physical scarce resource that the self has full unencumbered agency over and responsibility for, rooted in our own bodies and then expanding out from there using organisation.

User interface

The most general software application has the most general use-case, something like "life assistant". This would be an application that is as transparent as possible in terms of getting things done in it, and it's so general that it can help with absolutely anything you do. It's not hard to imagine this now that AI has very general agency.

A universal middleware is essentially a "universal connector" and "translator" that allows the connection of diverse informational representations into groups. An LLM of about the CHatGPT-3.5 level already make extremely good universal connectors which means that we already have the ability to create a unified ontology of our information lives that is continuously kept up to date with actual state and can act as an interface to the connected things, in other words, a self-organisation structure.

It's easy to imagine an up-to-date and complete information representation of our lives, because we already have various folder structures and other informational interfaces connecting us with a big part of our lives. Often times we're acutely aware of how fragmented our informational life is, and long for the convenience of seamless connectivity between all the aspects of our informational lives.

From the system's perspective, even human users are just another form of connection instance. Communications with users occurs in the form of user interface sessions which are themselves composed of user experiences and user stories. The connector is agnostic to the specific medium, interface language, style and preference involved in a user connection.

These connections participate in groups which we call organisations even if they're just a static informational group because, no matter their simplicity, they all have the potential to evolve into any complexity of organisation.

Organisations depend on resource such as materials, attention from people filling roles, executional focus etc. Even a simple static file requires storage space, and reading it requires bandwidth and attention.

The dependency on resource creates a hierarchy with the largest resource/energy reservoirs at the top, allocating resource to their primary salient categories of usage. The most logical root for this hierarchy is the user themselves, the "home folder" that always represents their present state.

This is what we call self-organisation, our own lives represented as an organisational structure which is continuously fitted to match our present state. A specific form of universal middleware concept.

The organisation-centric nature of the holon means that the model revolves around very fundamental concepts that organisations are defined in terms of, such as resources, processes, knowledge, development, roles, production etc. When we talk about society and economy, we're in the specific context of a society of self-organisations exchanging resources and behaviour patterns. These organisational concepts are the focus of the following system description.

Our holarchy project

The structure is rooted in oneself to reflect the fact that we're all the permanent centre of our own lives (experiential structures). This means that by default, all external exchanges and decisions will be optimising for self primarily. This is natural and is actually necessary, but unconditional maximisation is not at all optimal. Comparing different strategies for guiding our external interactions is a philosophical discussion which is beyond the scope article, but suffice to say here that we believe holarchy is the most rational strategy.

Holarchy is generally considered as a philosophical framework of attributes a system should have in order to be aligned with the principles we observe in living systems. It's usually presented as more of a set of guidelines than a specific system definition.

Here at Organic Design we believe that there is a simple organisational structure at the heart of and common to all living systems, and even underpinning consciousness itself.

We believe that holarchy is a very definite and describable system. It's in the form of a cognitive architecture following the self-organisation concept described above. Holarchy comes with a definite strategy for the aforementioned external connection issue, which optimises for both self and whole; i.e. its self-assertive and integrative behaviours.

We're researching and developing the holarchy concept in the form of a peer-to-peer network of self-organising holons. We're currently attempting to articulate the holarchy concept with enough detail and clarity to define a software design pattern from it.

On the research side of the project, we extend out to a wider focus than the development to encompass the philosophical aspects of holarchy. The political philosophy perspective concerning the kinds of large-scale social order and progress that the holarchy system of organisation implies. And foundational ontological perspective of seeing holarchy as a foundation for cognition and even of reality.

The project's development effort can be broken into three general areas: the p2p network architecture, the holarchy organisational system and AI integration. The purpose of this article is to introduce these three aspects starting with its peer-to-peer foundation. And following them at the end, we discuss the some high-level organisational patterns and use-cases for the system.

This project is our attempt at articulating the holarchy concept, operating our own organisation, projects and lives in accord with it, and presenting it in the most understandable, resilient, reproducible and usable form that we can.

Peer-to-peer network development

Holarchy is inherently peer-to-peer in nature due to all nodes at every level being holons embodying both individual and collective oriented behaviours.

Peer-to-peer networks are a kind of network where there is only one kind of participant which can interact in both client-like and server-like ways. This means a peer-to-peer network is a more general architecture than client-server, and also that peer-to-peer is not opposed to client-server, it can dynamically represent client-server in response to the right conditions.

In more general terms, we can say that the peer-to-peer pattern is a group-pattern whereby all members are both independent participants as well as maintaining a shared state together. Knowledge gained locally is merged into the shared context and is available to guide all participants. This creates a feedback loop so that both individual and collective sides are continuously co-evolving.

We were not able to find any existing libre software project that we felt really catered for the holarchy's specific networking requirements, so we've spent the last few years developing a custom solution based mainly on LibP2P, IPFS and Welo. It's a fully libre software solution which can be used independently of the holarchy, for use cases such as a decentralised content distribution network or distributed backup system.

Universal filesystem

One of the main roles of the holarchy is as a general resource allocation system, and the bandwidth and storage that connects holons into the holarchy are amongst the resources that are managed organisationally by the holarchy itself.

This means that the networking layer for the holarchy should ideally be transport, technology and storage agnostic. Presenting a common networking ability that's aligned with the architecture of the holarchy, and is able to dynamically incorporate into a common interface all kinds of network and storage resources that are made available to it.

The network layer needs to be able to provide the holarchy layer above with the ability to allocate and prioritise these bandwidth and storage resources flexibly in accord with the needs of the complex organisational structures that holons can represent.

A universal middleware needs a universal filesystem. A common interface through which all of the organisation's informational content can be managed and distributed.

Mesh networking

The most pure p2p architecture is the mesh network, it's the most general of all networking architectures because it is the most ontologically fundamental. It can function under the most restrictive and unreliable environments. The peers in a p2p network can support higher levels of abstraction allowing groups of peers to behave as a different topology such as a client-server network with the associated gains in efficiency, but client-server cannot behave in a peer-to-peer way without losing efficiency.

The most extreme degraded state of network is no network at all. When a network's peers can continue to operate even when completely isolated, it's said to be an offline-first network. Obviously there will be much less capabilities available in an offline state, but the idea is that local organisations operate with cache and "outbox" patterns of behaviour. This allows continuous local operation that synchronises with the wider community as circumstances permit.

The highest level of organisation in IT infrastructure is something like Kubernetes running in the cloud. Any application can be deployed at the click of a button, and the hardware supporting the deployment can scale up and down in real-time to meet demand dynamically throughout the network.

Since a mesh networking system is able to function in such a broad range of environments, it serves well as a glue for combining physical infrastructures and transports. For example, being able to expand the mesh over bluetooth or carrier pidgin.

Offline-first design

Back in the 90's when bandwidth was scarce and costly, we made heavy use of the "outbox" in our email programs. We would go through our inboxes replying to messages and composing new messages, and we'd be offline the whole time. Only when we'd finished writing the messages would we finally connect to the internet, hit "send and receive" and then disconnect again as soon as it was finished transferring data. We'd usually have a cup of coffee while the system laboured away transferring all those kilobytes.

Most of the time, offline systems are not necessary these days, and so software is written with the assumption of a permanent network connection, for example by depending on domain-name resolution or other network services. Most of the time this is not a problem, but in those situations where it is a problem, it's a really big problem because most of the software is completely incapacitated.

For example, nearly all of our favourite chat programs will fail even to send messages between the locals on the same LAN if the internet connection goes down. Many of these programs will not even start up without a connection.

Peer-to-peer systems are much easier to design in an offline-first way than client-server systems are, because they're designed to operate responsively regardless of peers spontaneously coming and going (a phenomena called "churn").

Since the philosophy of the holarchy supports local independence and sovereignty, and because it's naturally peer-to-peer in structure, it's a natural decision to aim for an offline-first solution.

The offline-first aspect also plays a key role in deployment of the system. The system will use its own package-style organisation to manage itself as a set of deployable packages and variations. Being inherently offline-first, the packages are usable, scalable and spreadable no matter how basic the situation they're booted into.

Not only is the offline-first paradigm more independent and resilient, it's also more responsive, resource efficient, accessible and shareable.

The offline-first approach is the perfect compliment to mesh-networking. Mesh-networking is about interacting with a diverse variety of networking resources and dynamically changing connections or reallocating resources, which means that it needs operational layer of the system to be decoupled from the underlying networking. This decoupling is exactly what offline-first provides.

Independence and resilience

We've discussed network-based independence already, but the system also supports some other important dimensions of independence which we give a very brief overview of here. Although these dimensions are not directly related to the networking, the peer-to-peer model in general enables far greater independence, resilience and adaptability.

The Libre software movement which advocates that the community should have access to software for all its needs which is free, open source, understandable and adjustable to local needs. All the software we're building and depend on is libre software. It's developed right from the seed concept as libre software, not that it will eventually be opened up after a particular stable release or after critical mass is reached. The holarchy itself is also all about the sharing, transparency and understanding of knowledge too.

Data sovereignty is inherently supported by decentralised models, because the most critical data needs to be the most local to ensure uninterrupted operation when problems occur in the wider operational context. Data sovereignty means having full control over this local data, just as one would expect to have over other private property.

Having local access to AI is a really important aspect of our system. It's currently not quite economically feasible as it costs around USD10K for hardware capable of running an AI agent that can play the role of a holarchy assistant (we'll come back to this later). All aspects of any AI we use locally must be completely libre software including all the training material and processes, because it needs to be completely trustworthy and unbiased.

The most fundamental aspect of independence concerns our survival needs, and so the real-world holons composing our own internal experimental holarchy are projects focused on land, energy, food, water and the sharing of permaculture, planting and off-grid living knowledge.

The four-quadrant holon model

The purpose of the holarchy is not only individual self-organisation, but about the whole network self-organising as a harmonious self-organisation (holarchy) of self-organisations (holons).

Our four-quadrant holon model proceeds from Koestler's four concepts of the integrative (collective) and self-assertive (individual) behaviours, and the fixed-rules and flexible-strategies mapped onto an orthogonal pair of axes. The aforementioned concepts map respectively onto the top, bottom, left and right directions of these axes which we call the "primary" axes.

The quadrants are the four corners delineated by the primary axes, and reside at the ends of a pair of orthogonal diagonal axes. These diagonal axes each connect two quadrants together into the feedback loops that express the evolutionary and economic behaviours. We'll come back to the diagonals and their feedback loops further on in the article.

The quadrants are like autonomous organisational "departments" that all holons have, which ensure that they all organise themselves and collaboratively support the whole collective network in alignment and harmony. The holons can be composed into organisational structure of any scale and complexity. The four quadrants are common to all holons, and therefore to all organisational structure representable by holons.

This means the quadrants are extremely general fundamental concepts having a strong philosophical connection. We believe this pattern of precisely these four meanings are inherent to meaning itself (the meaning-making process), and are epistemically convergent, or in other words all contexts involving sufficient intelligence would eventually discover this specific pattern. It's no surprise therefore that we see these four meanings pop up together in many traditions throughout history, such as in the form of Aristotle's "four causes" or in philosophical Taoism which are both thousands of years old.

Perhaps the most recent incarnation of the four quadrants is Ken Wilbur's Integral Theory that's gained popularity in the last couple of decades. The quadrants in our model correspond precisely with the four quadrants of Integral Theory, but in our model the positioning of the quadrants is vertically flipped from Integral Theory. The justification for this flippage is that for our purpose, the most important attribute of "above" is its natural relation to wider scope (outward, encompassing more, collective), and conversely the natural relation of "below" to narrower scope which is more specific and deeper within. Note also that Ken Wilbur mentions the concept of an "integral holon" in some of his writing, but we're currently unsure whether his concept follows the same mapping to Koestler's core holon concepts as our model, if it does then we'd prefer to use the term "integral holon" too.

Our holon model is a refinement of Koestler's general concept which has been designed specifically for the information technology context. To define a software specification, the quadrants need to be understood in terms of specific system interactions. We introduce this refined view of the quadrants in this section, but we also have a more in depth and complete description in the holon mechanism article.

Before we start talking about the quadrants specifically, we need to introduce the concept of a cognitive architecture and some other software design patterns that our model embodies. We'll then be in a good position to discuss what exactly these four "organisational departments" of a holon do.

Cognitive architecture

The general context of the pattern is the self-organisation concept described above, and more specifically it takes the form of an agency-agnostic cognitive architecture, i.e. any agency can participate regardless of its attributes such as simplicity or complexity.

A cognitive architecture is a systemic foundation for agency which defines the environment it finds itself to be within. It gives participating agents a local subjective lens or point-of-view (POV) through which to perceive reality. The cognitive architecture defines the universe of possible content and interaction available to any agent operating in accord with it.

The dynamic that takes place within this subjective individual point of view corresponds to Koestler's self-assertive behaviour. And the dynamic that occurs outside of it is the objective collective behaviour which corresponds to Koestler's integrative behaviour.

Agency

We use the word "agency" to refer to the ability to apprehend state and instructions and perform any actions that may be implied by them.

An "agent" is an actual entity of some kind which has agency, it has the ability to perform various specific roles when called upon in appropriate circumstances. Such an agent might be a user, an AI, an API or OS, a domain-specific language interpreter or many other things. An agent is an agent of change, there is no agentic focus without corresponding activity.

The holarchy is an organisational system which is agency centric since it's a cognitive architecture, but yet it's also agency agnostic, which means that it interacts with any kind of agency in the same way - in the same way as our system of law applies completely to people, but yet is (ideally) person agnostic in its application. This includes being agnostic to whether the agent is simple or complex, or whether its focus is discrete or continuous in nature (i.e. whether it should be treated in a multiplexed or multi-threaded manner).

Regardless of their agentic complexity, it's fair to say that all instances have a subjective local point of view consisting of the information and threads of activity within their local instance scope. They find themselves to be in an organisational context consisting of other sibling instances of various classes encapsulating their agency within and presenting their state publicly to be apprehended by the other siblings.

In terms of information systems, agency represents the ability to execute code, and in organisations it represents the ability to fill a role and perform procedures in it. All change in a holon is due to agents changing local state by performing activities.

Focus

The holon is itself a group of holons which we call siblings. All the siblings find themselves together in a private informational context through which they can express themselves to each other. The context represents a particular objective that the siblings collaborate together on, and which is provided by the holon - the parent of the sibling group which the group are in service of. In IT terms we'd say that all the siblings are parallel child threads in a shared private scope owned by the parent object.

The focus is the combination of content and thread aspects of system execution. It is the actualised content in the present moment in the context of a particular sibling (that is visible and accessible by the sibling).

The focus occupies a "moment" (also "session" or "slot") in time, the duration is context-dependent for example on the type of agency involved. During this moment the agent performs an action determined by the current condition of shared local context.

Scope

In information technology, the term "scope" refers to the names that can be locally referred to by a process. The context mentioned above that agency finds itself within is called "private" scope, and consists of a list of sibling names, other things that "reside" within that same scope, such as information and other agents, which are said to be "local" to each other.

We also have "public" scope, which is the names that are made available to the parent context. And "non-local" scope which is network-wide and will be introduced further on.

Salience

Focus applies to the present moment and refers to the energy that brings the present moment into being in a particular scope allowing an action to be performed. Salience refers to what will receive focus due to being instantiated ("installed" into the local scope) or "connected into time". Salient things are "in our field of awareness".

Salience and agency go hand-in-hand as neither are meaningful without the other. In terms of organisation, salience is the types of activities (behaviours) that may need to performed, and agency is the ability to actually perform them. Roles that may need to be filled, and those able to fill the roles.

Activity

Focus and activity go hand in hand, all focus is in the form of activity being performed. A holon as a whole is a continuous timeline made up from structured threads of activity. A single action occurs in single moment of focus, and the whole stream of activities makes up a thread of "experience".

Focus is always within the context of an activity in a particular state of progress or completion. The top-level activity aspect of a holon is constituted from a future component above, a past component below and the present in the middle.

Activities have a "lifecycle", they start off initially as just intention without any commitment of resource externally. Eventually they reach a mature enough state that they start to form commitment where actual roles and resources become involved. Once such resources are "filled in" sufficiently, aspects of the activity become imminent ("booked into schedules"). Eventually they make their way down into the present where they become active in production generating accounts of completed (past) activity with corresponding state and reputational changes. And finally their informational aspect is integrated both locally and beyond.

Self representation

• maybe remove this whole section, or merge into ai/curation
• self-organisation is the default purpose, so fitting the local representational-state to objectives and reality is a default objective
• BR is the actual cache built from the immutable past, so this is the quadrant we focus on here
• An instance has one scope containing one representation, and every representation and its scope pertain to one specific instance.

The multiplexed trees define the specific data structure, dynamic scope and rule-based production environment.

The state of a holon-instance is the informational content contained within the instance's scope. Since an instance involves three kinds of scope (public, private and non-local), it also contains three kinds of state corresponding to them. We refer to these three aspects of state all together as simply state.

The private and public state together are called the foreground-state. They're the values associated with the unique names constituting the instance's private and public scope, which is really just a single scope, private by default, but may have any amount of it marked as publicly accessible.

The non-local aspect of state, also called class-state, background-state or default-state, is the state that the instance has as default by virtue of its class (or more precisely, by virtue of the internal class structure that the class defines). Any local foreground state overrides the default structure and state provided by the class. This is essentially the same way that instances extend and override their classes in traditional OOP.

A holon's state is a continuously maintained self-representation, an abstract version of its real-world counterpart. An information structure that represents the holon's instantiated behaviours and the state of the real resource under its ownership and control. The instance state is just like it is in traditional OOP, except that the its structure and continuity are handled differently which we'll cover below.

• state structure

The representation is bidirectional, on one hand it's always changing to reflect the current state of reality, and on the other it's being used as an interface through which intentions are expressed in accord with the body schema pattern.

• API results maintained as an ontologically structured cache
• The change of state events that are received from connections to real state (such as an API end point or file event) are translated to the representation including various layers of abstraction such as reports, queries and format conversions.

An instance is an informational structure which follows the pattern determined by its class, and also represents something specific in the real world. Any organisation follows this same familiar pattern, they're are abstract patterns that we use to manage our resources and information together in society. So the informational structure of an instance is a representation of both the class and of actual resources that fall within its designated objectives.

Its important to note that the representation is not the actual resource, but rather an abstraction of it. The holarchy does not directly contain any of the resources that are being organised by it, rather it contains metadata about the resource. Imagine a spreadsheet of our finances for example, the specific file in question is an instance that represents some financial state in the real world such as bank transactions and balances. This spreadsheet instance also represents a definite spreadsheet idea that determines the structure and methods available in the context of any spreadsheet instance.

The operational work of an instance is to use informational connections to resources to maintain a representation that is ontologically structured in accord with the class. The state of the structure is continuously fitted to the real state of the resource outside the holarchy.

Instances use this representational mechanism to serve as interfaces allowing us to interact with and organise our information and resources using an evolutionary ecosystem of established organisational patterns.

First-class citizens

In the context of programming languages, a first-class citizen is an entity which supports all the operations generally available to other entities. These operations typically include being passed as an argument, returned from a function, and assigned to a variable. In most OOP contexts, objects are first-class citizens, meaning they can be instantiated, manipulated, and passed around in the code just like other basic data types.

The holarchy is not a programming language or OOP environment in the traditional sense, since it's a higher level of organisation based on general cognitive agency. But we use the term regarding holons to imply that every holon instance has all the same inherent four-quadrant form as every other holon instance, regardless of it's depth in the hierarchy of instances, its complexity or simplicity.

First-class citizens are all equal in the sense that they could all evolve into anything else, all essentially have the potential of becoming any other.

Knowledge and patterns

Knowledge is an important aspect of any cognitive architecture. There are quite a few common attributes to knowledge. It represents behaviour patterns, can be communicated, learned, embodied, taught, used, adapted and assessed.

It's a concept that depends on community. In a community context, the assessment, adaptation and selection of knowledge leads to an inherent evolutionary aspect to knowledge. In fact knowledge, language, community and evolution are all interdependent aspects of a single fundamental cognitive behaviour pattern.

For our purposes, "behaviour pattern", "design pattern" or simply "pattern" are synonymous, they're just operating at different scales.

Software design patterns are tried-and-tested solutions to common software design problems. They represent best practices, not in terms of writing specific lines of code, but in conceptual terms of organising entities and their interactions to achieve certain design goals. Think of them as templates or blueprints that can be adapted to individual needs, irrespective of the specific technology or language being used.

In other words patterns are things which are understood and acted upon by some form of agency. Different domains of patterns relate to different forms of agency, but they're all inherently the same thing.

Production rule pattern

The lifecycle of an activity might simply consist of a single session of a single agent's focus, or it could be a very complex hierarchical structure of projects and roles that activate under specific local conditions throughout time. Activities can be in a variety of organisational forms all determined by their structure, such as continuously developing, reoccurring, one-off, conditional, pipelines and cyclical.

Rules can be composed into complex workflow structures, allowing for the expression of complex logical relationships. Production rules are widely used in expert systems, business rules engines, and knowledge-based applications.

Production rules play an important role in automating decision-making processes, enabling systems to make reasoned choices, offer recommendations, and adapt to changing circumstances based on the knowledge encapsulated in these rules.

The production rule pattern provides a powerful means to represent systems and knowledge that may take all these myriad forms. A production rule consists of two essential parts: conditions and actions.

The rules themselves are in a form that is understandable and actionable by the relevant local agency. There is nothing in the rule content that refers to control-flow or workflow, the flow of focus is determined entirely by the structure of rule composition. In fact it's this lack of reference to control-flow (called a declarative execution paradigm) that gives production rules an inherent composability with each other.

It's the structure of the production rules that defines the conceptual meaning of the organisation, not the agent-oriented content of its production rules. In our system the rules follow the self-organisational structure introduced above.

This pattern allows complex workflow (organisation, control-flow, program execution, process) to be intuitively understandable without specialist knowledge about the workflow mechanism itself.

Blackboard pattern

This local scope that agents find themselves within when they receive attentional focus follows the blackboard design pattern of execution which, in the case of a holon, goes hand-in-hand with the production rule pattern. The blackboard pattern is akin to experts collaborating together around a blackboard, where they each contribute insights toward solving a complex problem.

It's a way to harness collective intelligence in systems with multiple agents, each with specific abilities. This modular and flexible approach allows for emergent solutions and the leveraging of specialised expertise without requiring any single agent to solve the problem alone.

It's widely used in artificial intelligence and distributed computing for its adaptability and collaborative problem-solving capabilities. It's also often chosen for its decoupled approach where agents can collaborate on a problem without needing to coordinate directly with each other.

The organisation that takes place within a biological cell bears striking resemblance to the blackboard pattern, especially when combined with the production rule pattern. The cell essentially defines a local private scope containing resources and enzymes, which is like the private blackboard shared by a set of relevant sibling agents. And the conditions matching relevant actions is like the cell expressing or suppressing particular behaviours in response to it's immediate needs (by dynamically regulating its biochemical pathways and functions in response to environmental conditions).

Workflow and behaviour

What we've been discussing with the blackboard and production-rules is often referred to as "workflow" or "organisation". It's not really referred to as a software design pattern, because it's quite a general concept. It concerns primarily process description and execution. Using the term "workflow" (or "organisation") rather than "execution" or "process" implies operation at a high level of abstraction.

Traditionally production rules are considered to be very discrete in their function, for example the condition part is considered to be similar to an "if-then" statement. But by implementing the production rules in their own private persistent scope as per the blackboard pattern, the rules are permitted to operate asynchronously. The blackboard pattern decouples the agents (knowledge sources) from each other so that they're free to interact via the scope in their own time. This makes the workflow much more flexible so that it can represent complex patterns of behaviour.

Knowledge is shareable behaviour patterns, production-rule sets in the form of condition:action pairs. Each pair is a feedback loop with the local environment which can be thought of as the generalised continuous version of a traditional production rule. These design patterns all working together form a kind of continuous workflow and improvement paradigm.

Class-instance pattern

• interface and abstraction missing here
• C&I is the abstraction of abstraction, meta-abstraction

When we say "patterns of behaviour" we're drawing on the fundamental concepts of "class" and "instance". The term "pattern" implies the ability to repeat a behaviour, refer to it and communicate it. The term also implies composition and structure which, as discussed above, production rules and behaviours are compatible with.

Class and instance are two interdependent concepts which are essentially another software design pattern, although they're so ubiquitous that they're an inherent part of the design of most programming languages, and so are rarely called a design pattern. We'll call them a pattern here, because we're defining our own specific version of the concepts that depend on the software environment for only very basic data-structure capability (one which can support the aforementioned workflow concept).

This pattern is really a "meta-pattern", it encapsulates the concepts of defining and re-using patterns of behaviour or functionality. A class is an abstract "package" of functionality defining how the package would function if it were represented by some actual functional resource - i.e. how a local instance of it would behave.

A "class" is essentially a name (also reference or identifier) that refers to a specific abstract grouping of other class-names, and "instance" refers to a specific "pool" of actual operational resource that is arranged in such a way as to represent classes in its operation. Classes represent sets of related behaviours, whereas instances are groups of actual agents capable of performing behaviours along with its current state of development.

The class aspect of a holon is analogous to Koestler's fixed rules concept, it defines structured possibility space within which instances can select and enact appropriate activities from all the possible ones. In other words, classes define how an instance of it would behave if various conditions were the case.

The instance aspect corresponds to Koestler's flexible strategies, where the behaviours that are expressed match the present local conditions.

We started this section on knowledge and patterns by saying that knowledge, language, community and evolution are all interdependent aspects of a single fundamental cognitive behaviour pattern. All these design patterns working together play a big part in connecting all these aspects into a single system, and we're now ready to start talking about the four quadrants which are the form that this single system takes.

A class is a particular behaviour pattern, and an instance is a class that is actualised by performed and represented by actual real resource. Classes specify collections of resource and agency types and the organisational patterns they would engage in if they were instantiated. Instance is an actual real collection of such resources and agents that have embodied the class pattern and represent it in actual state and process.

Three abstraction layers

An abstraction layer is a conceptual framework or set of functions that hides the complexities of lower-level operations, allowing users to interact with a system or software component in a simplified and standardised manner. It serves as a bridge between different levels of a system, enabling efficient communication and interaction while shielding users from the underlying technical details. Abstraction layers are commonly employed in software development to promote modularity, scalability, and ease of use.

In a running system, each layer can be seen from an instance perspective as being a society of instances that all interact together via a common set of interfaces. Interfaces are "provided" and "used" just like the client-server model.

In the running system, these layers are logically independent (but they are not conceptually or economically independent), each layer defines new interfaces that hide its own complexity within. The instances composing a running layer are free to collaborate fully on the content and evolution of their "user space" independently, the parent layer does not interfere with a child layer.

Our model has three abstraction layers. The the first (L1), is the process that results in the class-and-instance environment, that within which the second abstraction layer operates.

The class content (non-local, "background") is formed as an aggregate of the forms of all the instances of that class. In the main model diagram, this layer is comprised of the horizontal and vertical axes, or "primary" axes.

The vertical is considered the primary of the two, and represents the instance concept. The horizontal is secondary and derived from the first and represents the class concept. Together they produce the class-instance environment for the next layer to build upon and extend.

The second layer (L2) is the "subjective" perspective from inside the instance's private scope. In other words it's a new abstraction layer occupying the "user space" defined by the first layer, the usage of the class-and-instance concept.

The second layer is where the four quadrants (by which the model itself is usually referred to) reside. Layer two occurs within the diagonal axes in the model diagram. These diagonals represent the fundamental systems of evolution and economy. The four quadrants, as well as forming the two diagonal feedback loops, are like departments operating independently within an organisation all aligned in their overall purpose.

The third layer (L3) is the space of full holons (self-organisations). This new layer occupies the "user space" defined by the second layer. This is the layer of arbitrarily complex meaning. In this environment, all content self-organises and progresses as an evolving society of organisations, a holarchy of holons. Holons in layer three are the users of layer two's quadrant system.

The third layer is an independent self-organising self-evolving society of holons. All holons are self-sovereign first-class citizens, completely independent and autonomous, but at the same time they all holons inherently represent the first two layers in their behaviour.

Layer 1: The primary axes

In terms of functionality, the first layer brings about the class and instance environment discussed above. This is essentially the layer that defines the process of abstraction itself by which subsequent layers are possible.

But in this section, we're concerned with the model not the functionality. The class and instance mechanism results in a number of important fundamental concepts which also form the most general characteristics for subsequent layers. These concepts are represented as the primary (vertical and horizontal) axis pair, which are shown in the image to the right, and are also depicted as the blue "+" in the diagram of layers above.

All concepts that make up the holon model are dichotomies, so in any scope of concern in the model, there's always a clear conceptual division into complimentary pairs. The axes correspond to the self-assertive and integrative behaviours of the holon, and diagonal pairs of the second layer, which are derived from the first layer pair, also inherit this correspondence.

The primary axes are a pair, and each of them has a pair of ends. Most of the traditions involving the four quadrants also talk extensively about the dichotomous origins, such as Taoism with its fundamental Yin and Yang dichotomy.

The four quadrant system informs and responds to change, but is not the ultimate actualisor of it. The system does not define change itself, it only organises it ontologically to be utilised by the actual agents of change. In terms of the diagram, the change occurs in the centre as an action representing the current class and instance within the horizontal axis. Vertically change is attentional focus in the local subjective context between outside (top) and inside (bottom).

The operations that bring about the primary axes of scope with focus are the first abstraction layer of the holon model. Both subsequent layers inherit these fundamental conceptual directions with current focus at the centre. Each layer builds upon the concepts of the prior rather than replacing them.

Both concepts take the form of a scope (namespace) concept with the positive end representing being not within the scope, and the negative side being within it.

The first kind of scope is the usual public/private vertical dimension that we're used to with an object from OOP, these are instance scope forming the instance tree. The second kind of scope, which is complimentary in its operation to the first, are class scope making up the class tree.

Within this primary axis pair, the instance tree is the primary or original axis and the class tree is derived from it. Even though instances are instantiated from and guided by their classes, they depend entirely on the instances to represent them, because only the instance actually exist by being backed by real resource.

The top is public, the bottom is private, the left is abstract and the right is actual. Each primary direction defines behaviour that is common to a pair of quadrants. Following is a short introduction to each of these primary directions.

Top (public collective)

Top represents the integrative behaviour of the holon that contributes "unconsciously" to the collective. The top is the interface between the holon and the outside world.

The collective unconscious (ontology, culture) and the material state of resource flow (society), it's the scope outside the holon's subjective perspective that maintains the network as a whole.

The top pair of quadrants both progress the public scope, the left in the form of evolutionary progress of knowledge and the right as the flow of resource exchange progressing over linear time.

Bottom (private individual)

The bottom represents the self-assertive behaviour of individual autonomy, which in our system means taking the form of a control loop. This is the perspective from within the holon's private subjective scope. The subjective scope is production rule oriented, and represents the self-development and production aspects of the holon. In terms of time, the bottom represents the past that has been created through operation and development.

Private scope consists of a list of sibling names which are all things that "reside" within that same scope, such as information and other agents. The contents of the private scope are "local" to each other.

The bottom quadrant pair both operate as a control loop which continuously brings the local scope to a better state.

The self-assertive behaviour takes the form of a self-representation state which is continuously "fitted" to reality, and also allows the expression of objectives.

Left (abstract class)

The left represents the abstract world which we call class, but it's also Koestler's fixed rules and represents structure, knowledge and possibility. In terms of time, the left represents, the cyclic nature of abstract behavioural patterns (spectrum that's orthogonal to linear time).

Right (actualised instance)

The right represents the concrete actualised world inside of time which we call "instance". This is Koestler's flexible strategies and represents day-to-day organisation, exchange and operation. In terms of time, the right represents the visible world of actual resource flowing within linear time.

Layer 2: The four quadrants

The four quadrants occupy the second abstraction layer of the model. As discussed above, the first layer primary axes define the most general contextual features for the four quadrants - what scopes they operate within, and the meanings that the upper, lower, left and right sides have.

The first layer made possible a new subjective local perspective, and the second layer is halfway between these two perspective, having "a foot in each side". The lower quadrants represent the inner local subjective perspective, and the upper quadrants represent the outer non-local perspective.

We often refer to layer two as the "objective-subjective", because it's an objective "unconscious" process like layer one, but it occurs in the local subjective scope. The third layer also takes place in this subjective scope, but all change is carried out by agency.

The inherent form of the quadrants is that they're grouped into a pair of feedback loops connecting diagonally opposite quadrants. These are the evolutionary loop and the economic loop. We use the word "inherent" because the information flow that defines these diagonal feedback loops between opposite quadrants are created by the first layer mechanism. The mechanism itself is beyond the scope of this article, what we cover herein is the meaning of these scopes and loops.

Before we go into any detail about the diagonals, we need to have a clear conceptual understanding of the individual quadrants. The easiest way to introduce the quadrants is to start with the already-familiar class and instance concepts on the left and the right respectively, and then divide them into an upper collectivised version of the pair and an individuated version below. The image to the right demonstrates this with the original class-instance axis horizontally in the middle.

The top quadrants represent the local holon's perception of, and contribution to, the whole tree (graph) of classes and instances, which we call "ontology" and "market" respectively. Since it's a bottom-up peer-to-peer architecture, these collective-oriented top quadrants are not the whole itself (which would have to be "centrally served"), they're a local representation of the whole from the local subjective perspective with self at the centre.

The bottom quadrants represent the local holon's internal private world. This lower pair is conceptually more fine-grained than the general (and abstract) class-and-instance concept represented by the horizontal axis. They represent the local subjective meaning of the class and instance dynamic. Classes are designed to be instances, their utility and purpose comes from how they behave within their subjective instantiated contexts. The internal class quadrant in the bottom-left is called "development" and it takes the form of conditional structure (the condition aspect of the production rule structure). The internal instance quadrant in the bottom-right is called "production" and represents the holon as a progressing activity (the action aspect of the production rules).

Each of the quadrants is delineated by the vertical and horizontal axes of the first layer discussed above. This means they each represent a pair of scopes, one from each primary axis. This gives us a clear foundation from which to derive the meaning and process for each quadrant that forms its concept of progress.

Since the processes are operating on the same state (all being aspects of the same holon), they must be complimentary and non-destructive to each other. But as we've described, the de-coupled production rule and blackboard model gives us exactly the non-destructive process-form we need here.

The quadrants are "real" in the sense that in a running holon, each has a specific executional thread representing it, so that each receives it's own portion of the total executional focus available to that holon. Each quadrant is an important and permanent aspect of the holon as a whole, very much like a department in an organisation.

The holon as a whole represents structured state and its path forward through time, and each quadrant represents a different perspective on what "progress" means and how it expresses that form of progress with its local behaviours.

As discussed above, the foundation use-case of the holon is as a self-organisation system which was described as being a kind of "smart folder structure" that represents our lives informationally and also acts as an organisational interface to them.

The four quadrants are four different aspects of the "self-organisation application", the bottom two are the familiar for of class structure and actualised instance structure that we're used to, and which we would expect of the "smart folder structure".

But we're not just individuals, our lives take place in the collective context of culture and society. The top two quadrants represent the class and instance aspects in their "collectivised" forms of ontology and economy respectively connecting us with and present wider contexts of knowledge and the market ecosystem.

Introducing each quadrant

• todo: cut these sections down to summaries, no diagonals

Following a brief introduction to each of the four quadrants and their general roles and characters.

Top-left (ontology)

• this section needs cleaning up

This quadrant is the "collectivised" version of the class concept. It's a left quadrant, which means that it concerns abstract knowledge which is not actualised in time. It's also a top quadrant putting it in the public scope, which means it's a peer-to-peer collective contribution process. This quadrant is called "culture" in Integral Theory, and it's Aristotle's "formal cause", which is often described as a "blueprint".

This quadrant takes the form of an ontology of classes connected in a semantic network of dependence and relevance (a class-tree). We sometimes call this quadrant the institutional quadrant due to it being a source of guidance for instances to follow that is the aggregate-knowledge from all the instances of the class. The ontology is the map of the ecosystem of behaviours established in usage.

These grouping (dependency) relations as a whole form a large associative network. But from the perspective of any specific node, there is a "fan-out", a one-to-many hierarchy of dependent child nodes, and grand-children etc to any arbitrary depth. These hierarchical structures determine the form of instances.

In terms of the use-case aspect, this quadrant is the collective interface to the holon's knowledge. It's the local holons perspective of the knowledge in the form of associated behaviour patterns and a map of their attributes such as usage and performance metrics. Being from the local perspective, the ontology quadrant only includes knowledge that is embodied (to any extent) by the holon in question.

The self-organisation structure is completely unique and local in form and state, but yet is entirely composed of patterns that are established in the collective ontology. This means that the ontology itself is an abstract concept representing all patterns as the hypothetical merging of all local perspectives. Each actual quadrant embodies the ontology by contributing to the non-local collective structure of the patterns in use.

Knowledge is not just dead information, it needs to be embodied behaviourally. It applies to a group within which it's established in collective usage. The evolutionary aspect is essentially about sharing aggregated performance information associated with the conditions, i.e. the objective and circumstance requiring the activity. This is how the ontology represents usable collective knowledge from classes established in usage.

The institutional aspect is the organisational structure that forms around this collective intelligence making it navigable and accessible to all. It's essentially an informational portal maintained by the users of the knowledge, or in other words, a peer-to-peer institution.

The foundation information on which the institution is based is the collective non-local aggregate of all the knowledge (class) that undergone instantiation (local production and development) throughout the network.

All instances of like classes form into knowledge-sharing groups. In this way, every class in the ontology (global class graph) is a community and a map of all the instances of that class.

The knowledge is naturally shareable, because the group of all instances of one class are essentially a special-interest group - they all have interest in the same specialist knowledge associated with that specific class.

The purpose of knowledge is to be used. To use it requires it to be embodied by a holon, in the form of classes that are "installed" (connected into paths of potential focus) into the local environment where they can activate it (in the bottom-right quadrant) in response to appropriate local conditions as they arise. Knowledge is not just opinion, it's determined by how effectively it's used. For the ontology to assure utility, it must include this performance aspect with the knowledge and the performers of it.

The ontology is structured by class names, and contains information about how those classes perform as children filling roles in various classes of organisation. The result is an ontology of behaviours associated with actual ability to perform them. These are the abilities that back objectives making them actualisable (by instantiation, making them potential and then imminent).

Although this is the non-local (collectivised) ontology, it's important to remember that even though it's a view of the collective, it's still from the local perspective of an individual local holon. It's the non-local unified ontology, but from the perspective rooted in the current class (which is performing the current activity).

The ontology evolves in diversity and complexity as the instances develop themselves (bottom-left) and share their knowledge (bottom-right). It's a collective form of development which is an evolutionary loop rather than a control loop like the bottom quadrants use.

The ontology interacts with the bottom-right production quadrant, providing the institutional aspect to it. The ontology is the provider of behaviours (classes) and performers of them (instances), and offers knowledge and guidance to instances helping them instantiate and operate.

Bottom-right (production)

We call this the production quadrant which takes the form of a self-assertive control-loop maintaining the private self-representation since it's a bottom quadrant. Since it's on the right, it's actualised in time involving concrete resource. This is Integral Theory's "behavioural" quadrant and Aristotle's "efficient cause" which is the agent that brings something into being.

In terms of the self-organisation, this quadrant is responsible for maintaining local instance of the organisation operating in the local environment. It carries out the process that fit the local self-representation to the real state it represents, and allow it to act as an interface to it.

This quadrant involves the actual achievement of the holon's objectives (in the bottom-left). Production is a control-loop that reduces the difference between the current resource state and the expected state.

An actual agent has filled a role in the local context and performed behaviours towards achieving the various objectives. The holon has gained "experience" by putting its knowledge to use in service of the holons own private developing objectives in the bottom-left.

The holon's internal production and development are in the form of structured production rules, and the "production" quadrant is the action/activity side of the rules. In this aspect of the organisation, we're in the private scope of production using private property. Production takes the form of a control loop that continuously moves towards goals set by the bottom-left development (intention) quadrant.

This quadrant is all about past, because it's about the accounting of an activity after it's been performed. The final account on completion is signed and immutable and contributes to the ontology (top-left) which has the current condition at it's root. The information contributed to the ontology is the performance, the account compared to the initial expectation, in the context of the condition (parent) that it's responding to. In this way the local knowledge is contributed to where it's relevant.

The production quadrant represents the actual state of production of the holon, such as materials, access, stock, accounts etc including the state of completeness if applicable. This quadrant represents the actual performance of behaviour informationally which we call "accounts" (i.e. an accounts of activites). Performance of behaviour is carried out in accord with the top-left "ontology" quadrant, and final performance with respect to expectations is presented to the ontology for aggregation. The results of production contribute to the objectives in the bottom-left quadrant, as well as providing and consuming resources via the top-right quadrant.

Bottom-left (development)

This is a bottom quadrant so, like the bottom-right, it takes the form of a self-assertive control-loop in private scope within the holon. It's on the left so it concerns abstract knowledge that is not actualised in time. But unlike the bottom-right control-loop, this one concerns knowledge rather than resource. Here the holon is navigating in potential space, developing its knowledge, intentions and objectives. This is the structural aspect of the private self-representation, its embodied behavioural structure.

This is the "development" quadrant, and is called the "intentional" quadrant in Integral Theory (we often refer to it by that name as well). It's Aristotle's "final cause" or telos, the objective or purpose for which something is done or exists. For example, the telos of a knife would be to cut.

In terms of the self-organisation, this quadrant represents its conceptual structure, a specific structure of behaviours (production rules) defined to achieve specific local objectives in a specific state of salience and current conditions. In user terms, this represents the meaning of the organisation that informs development decisions.

The objectives are defined by the condition-side of the internal production rule structure, with the bottom-right "production" quadrant representing the action side of them.

Objectives concern the future and so this quadrant works in conjunction with the top-right resource-flow (market/economy) quadrant which is also about the future.

The development quadrant represents the holon's objectives in the form of a structure of embodied behaviours. This structure represents the embodied and salient aspect of the holon class behaviours from the ontology (top-left), backed by resource from the market (top-right) and attained by production (bottom-right).

Top-right (economy)

This quadrant is at the top so it's a collective contribution in public scope, and being on the right it's within the context of actualised linear time. We call this quadrant "economy", because its purpose is to harmoniously allocate limited resource amongst a potentially unlimited demand for resource. This is Integral Theory's "society" quadrant, and Aristotle's "material cause".

It seems at first glance that connecting the meanings of "economy", "society" and "material cause" across these systems is contrived to fit our designs. But remember that we're in the agent-centric organisational context of a holon, where "external material reality" is in purely resource-flow terms, and is the merging of all local perspectives. This quadrant represents the local state of resource-flow expressed in supply-demand terms by the instances occupying the public scope. The resource-flow effectively represents the total of all committed objectives. That is, the intentions expressed in all the bottom-left quadrants throughout the holarchy.

Essentially the economy concept describes a free market based resource allocation system used and supported by a network of autonomous participants. These entities have the autonomy to choose what goods or services to produce or consume, at what price, and from whom.

In terms of the self-organisation, this quadrant represents the interface between the public and private sides of the holon. Its organised by linear time in the future and so from the user perspective it takes the form of a schedule. The schedule is an organisational "container" in which roles and resources are "booked" by instances that fill the roles.

A holon requires real resource in order to function. In other words, the self-organisation structure represented by the bottom-left quadrant needs resource organised by the top-right quadrant to represent it. Such a representation exhibits expectation and after it's completed will exhibit performance with respect to it.

Objectives are defined in terms of external resource state in the future, and so this quadrant inherently relates the bottom-left development quadrant. This relationship takes the form of a feedback loop which we'll come back to below.

This quadrant allows the holon to participate in the wider market, all together forming the economy (the society of organisations).

The diagonals (⤫)

As is quite intuitive and can be seen in the diagram to the right, the quadrants naturally form a diagonal pair of axes. But the diagonals also represent the actual algorithmic/mechanistic connections between the quadrants too. We won't go into the details of the mechanism behind the formation of the four quadrants in this article, but the diagonals are one specific consequence of this mechanism which are important for our discussion here.

The functionality of the quadrants (from which their meanings are derived) takes the form of a pair of feedback loops connecting the diagonally opposite partners.

These two diagonal loops constitute dynamics of second abstraction layer of the model that refine the four quadrants behaviours and connect them all together into a harmonious whole.

The diagonals are the form of the "application" presented by level two for use by level three. Just as the class-and-instance mechanism was the level one provided for level two's use.

The diagonal relationships are due to the form of the diagonally opposite quadrants being complimentary so that each diagonal forms a feedback loop. The quadrants meanings derive from these feedback loops, and so in this section we look in more detail at these two loops.

The four quadrants occupy the corner areas delineated by the primary axes (vertical and horizontal), and so all quadrants are situated on the diagonal axes as shown in the image to the right. These axes represent the actual connections giving rise to the function of a holon.

The bottom two quadrants represent the familiar self-oriented organisational context. These each connect to their opposite outward partner, the bottom-left connects to the top-right in an economic loop, and the bottom-right connects to the top-left in an evolutionary loop.

Each loop is a distinct way the collective forms from the individual behaviour, and conversely how the individual is guided by the collective. Each is a co-evolutionary loop just like the first layer class-instance loop is.

Both loops are derived from and extend the primary feedback loop dynamic form into a new concept involving knowledge derived from the local internal scope. One diagonal extending the instance-tree and the other the class-tree.

In each loop-extension there is a rating (evaluation, feedback) of the associated tree involved. The economic loop involves a subjective rating in accord with local intentions and preferences, and the evolutionary loop involves the objective rating of local productive performance. Both loops involve local rating and non-local merging of the rating information. In both loops, local decision-making is guided by the non-local aggregate information.

The collective can be thought of as a "service provider" (albeit a non-local peer-to-peer one) that evolves with the clients needs, and the individual (as the client) is guided by and uses the service. The ontology is a service utilised by an agent in production, and the economy is a service utilised by a consumer.

Economic loop (⤢)

The diagonal consisting of the bottom-left and top-right quadrant (⤢) forms the economic loop and is associated with the self-assertive behaviour. It extends the first layer instance tree (represented by the primary vertical axis) which is inherently economic in nature due to representing the flow of real resource and attention through time.

The bottom-left quadrant represents the self-organisational structure, which is a structure of recurring behaviours. The top-right quadrant represents the schedule of committed resource that backs the performance of these behaviours.

The diagonal axis of the economic loop extends the first layer instance tree from a purely attentional flow to a more refined concept that includes the aggregate of local market knowledge coming from subjective value judgements and decision-making.

This axis represents the holons presenting itself in its self-assertive form in the public market. In other words, its public state as an autonomous self-organisation in the public market. This self-assertive expression of economic commitment, is the form that the aforementioned subjective rating takes. This is the subjective evaluation of instance, and expression of that evaluation through attentional (and resource) support. The directed support is how objectives are determined, the economic loop is results driven (declarative).

The foundation of the economy is the flow of attention, which is the salience landscape, the distribution of weights that determine the flow of focus throughout the instance structure. Salience is distributed internally (bottom-left) as the tentative virtual branches extending from what's represented in the resource flow (top-right).

From the user (self-organisation) perspective this diagonal represents the market interface. The organisational structure can publicly present supply and demand schedules of various resources. The holon presents various consumer and producer interfaces and states publicly. This is how commitments are made that permit actual production, and all together make up the whole resource-flow.

The economic loop is an organisational structure spanning internal behaviours as well as resource schedules. Salience is distributed across the structure, and directing this distribution over time is self-development. Organisational structure and its salience are the common form of the bottom-left and top-right quadrants.

The loop is a bidirectional instance-tree process of interaction between internal virtual instantiation (exploring a concept) and the public market of actual resources and value. The private virtual content is essentially a "replaying" and "remixing" mosaic of instances from the public arena.

The public content (the the flow of resource as a whole) which is the total of all the internal virtual instances in the whole network that have become backed by real resource (through persistent salience). In other words, a context starts as a purely abstract concept that can be explored and gain more focus and resource, becoming booked into public resource schedules.

The top-down side of the economic loop is the flow of focus and resource that determines which instances and conditions are active. The feedback flowing from the bottom up is intention, or subjective valuation of the context.

Evolutionary loop (⤡)

The diagonal consisting of the top-left and bottom-right quadrants (⤡) forms the evolutionary loop and is associated with the integrative behaviour. It extends the first layer class tree (represented by the primary horizontal axis) which is inherently ontological in nature due to representing the dependency and relevance relationships between classes.

The top-left is the ontology of behaviours, and the bottom-right is the actual performance, or usage of them in the local private production context. Both ends of the evolutionary loop concern the execution (imperative) aspect of the system in terms of utility and performance.

The ontology in its basic form is created in the first layer, based on volume of usage. Then in the second layer it's extended to include the performance metrics corresponding to the specific performers of the behaviours. This process expresses the principle that knowledge is not black and white, it's embodiment is proven and assessed through actual performance.

In this subjective inner context, the information being aggregated is the performance of the knowledge in-use internally. This aggregate knowledge is the performing-instance's "reputation" or potential effecting it's likelihood of being matched in the market again in the future.

In user or self-organisation terms, this diagonal is not so much an interface as a connection to relevant knowledge to help in deciding which performers the roles should be filled with.

The evolutionary loop is a bidirectional class-tree process of interaction between internal usage and execution of a behaviour and the institutional map of knowledge relating to the behaviour.

The top-down side of the evolutionary loop is the institutional knowledge and guidance (map) flowing inward from the collective class. The bottom-up feedback side is the objective performance (of the embodied knowledge) and usage statistics of local production in aggregate form.

Intersection of evolution and economy

The economic axis is primary, and the evolutionary axis is in the context set by it. This is because the former is extended from the first layer instance axis and the latter from the first layer class axis.

First the economic axis activates, the internal intentions are created in the bottom-left, and then are enabled by the backing of real resource in the top-right. The merging of the commitment schedules of many holons, creates potential for resource exchange leading to the whole resource-flow.

Then the evolutionary axis activates, the specific instances are selected from the top-left to perform in private production in the bottom-right. All other things being equal amongst candidate suppliers (performers) are prioritised according to their performance metrics. Actual performance takes place in the bottom-right and is fed back to refine the knowledge in the top-left.

This selection occurs diagrammatically in the centre where the two diagonal axes of class and instance cross. This is where the process that matches supply to demand, resulting in committed (contracts) resource backing the objectives over time takes place. The selection is based on the evaluation of the class and instance aspects. In other words how well the class is achieving its fundamental purpose of instantiation, and how well the instance is bringing value to the local context.

The first level provided the basic subjective context in which conceptual structure has a directional aspect. This leads to the self being at the centre in the here and now, with its subjective perspective of the world surrounding it. The second level extends the subjective context to include an inherent ability to assess things in terms of potential and performance, so that both the class and instance structures are continuously improving in their fundamental utility.

*   *   *

The diagonal loops (and the individual quadrants they're constituted from) have specific meanings that derive from their extension of the general meaning provided by the first abstraction layer, each progressing the holon in their own specific yet complimentary way as well as the class and instance structures as a whole continuously improving and evolving. The result is a holon which embodies a rich set of general organisational behaviours; it participates in the evolution of knowledge and the economy as well as progressing its individual knowledge and material position.

To expand on a key concept in the previous paragraph: the economic and evolutionary foundations present in the two diagonals have not been deliberately designed, they're inherently provided by the first layer structure. All we've done is naturally extend the first layer with its own dynamics in the subjective second layer and the diagonals naturally take on these meaningful dynamics.

Although the second layer concepts such as evolution, knowledge, expectation etc are very conceptually rich and complex compared to the first layer, they are a very basic version of the systems they represent (evolution and economy). The evolutionary loop boils down to the distribution and management of variations and selections, and the economic loop is a simple free market dynamic involving supply and demand commitments and schedules. They form a neutral conceptual foundation on top of which larger objectives and methodologies can be expressed.

The holon model acts as an "ontological wrapper" allowing any information, knowledge, systems or resources to be interacted with in universally understandable meaningful terms. Ontologically representing all the common organisational aspects of it such as the time period it covers, it's state of completion, behavioural or performance aspects, purpose or value.

Layer 3: Holonic self-organisation

The third abstraction layer in the system is the organisational environment - a self organising network of self-organisations. Every node making up the network of content in the third layer is a complete holon, and a first-class citizen. The third layer represents the user perspective since it's the layer representing interactions involving complete individuals. This layer is a society of organisations in which they all represent themselves as self-organisation structures all having the two loops and four quadrant aspects.

All the organisational functionality of the holon is latent in the fundamental class-and-instance mechanism and the general directional meanings defined by the first abstraction layer.

From the user's perspective, the top quadrants are seen as the public interface through which the local holon interacts with the collective. These top quadrants are like services provided by the collective (although the collective is the collaborative aggregate of all individual holons). The top-left is the "map" interface to the ontology as a service, and the top-right is the "schedule" interface for interacting with the flow of real resource.

The bottom quadrants revolve around our self-representation, the abstract ontological structure and informational state of our self-organisation. The structure changes through the holons development in the bottom-left quadrant, and the representation is kept up to date (fitted to reality) and progressed towards objectives by the production process in the bottom-right.

Assurances

The whole must assure (prove, demonstrate) that it effectively maximises the harmony, autonomy and potential for both the individuals and the whole. If it doesn't, then it's not truly worthy of their membership. The whole relies for its very existence on the support of its members, so its effectiveness and the evidence for it is the foundation of its own security.

The collective aspects are abstract, emerging from the many participating as network nodes. but yet it's this collective aspect that provides the assurances that are really the sole reason for participating.

The reason that participants choose to participate is because the holarchy offers assured benefits. It offers usable and reliable knowledge in the form of the ontology and offers opportunity and a harmonious environment in the form of the holarchy. The knowledge needs to be usable and reliable, in other words it needs to provide assurances of its utility.

The assurance of reliable knowledge is a bit more nuanced that what it sounds like. The holons are all contributing to a global state of institutional predictability, which concerns a stable operating environment in which plans can be made. The assurances come from the fact that the protocol itself objectively and unconditionally includes the integrative behaviour.

• incentive, expectations

Institutional predictability

Institutional predictability is the idea that all participants of a society have a reasonable expectation of how the society operates and how their actions will be governed. This predictability can include property rights, contract enforcement, and legal protections.

• institutional predictability is a fundamental objective of the holarchy model, because its fundamental to the ability to organise and plan
• how the organisational layer achieves institutional predictability
• institutional predictability - why the self-assertive supports the integrative

The quadrants in the third layer

Following is a short description of each quadrants from the third layer user perspective. For a more in depth description of each quadrant in terms of its connections and functionality, please refer to the second layer descriptions above.

Top-left (ontology)

The holarchy is essentially a service (and so should society be), like a p2p network serving an application to all the peers for them to use. The holons are users of the holarchy, interacting with it via an interface in sessions of activity.

The ontology from the user's perspective is a "service" or "institution" that maintains the structure of usable knowledge connected by relationships of dependence and relevance. How well the knowledge is embodied is maintained by the individual instances, and the aggregated and mapped for use by all instances of that same class.

The institution provides portal and search like interfaces assisting potential instances to find the classes and variations that most suit their local purposes and circumstances. It also provides the most useful and relevant knowledge and tools to assist with instantiation which is like "installing" the class into the local context as a continuously fitting instance.

The institutional aspect is the organisational structure that forms around the aggregated collective intelligence making it navigable and accessible to all. It's essentially an informational portal maintained by the users of the knowledge, or in other words, a peer-to-peer institution.

Top-right (economy)

This quadrant represents the interface between the public and private sides of the holon. Its organised by linear time in the future and so from the user perspective it takes the form of a schedule. The schedule is an organisational "container" in which roles and resources are "booked" by instances that fill the roles.

Bottom-right (production)

The production interface is about interacting with the representation in day-to-day operations.

Bottom-left (development)

• virtual instantiation, potential management and salience interface

This quadrant represents its conceptual structure, a specific structure of behaviours (production rules) defined to achieve specific local objectives in a specific state of salience and current conditions. In user terms, this represents the meaning of the organisation that informs development decisions.

*   *   *

The collective environment of knowledge is evolutionary, co-evolving with the holons, individual development and production within each holon being the source of change for the evolutionary process. This is the evolutionary diagonal loop formed from the bottom-left and top-right quadrants.

The environment is in the form of a dynamic mosaic of instances (the local instance tree), and the user's internal objectives are in the same terms, extending the external mosaic within making up the economic diagonal loop formed from the top-left and bottom-right quadrants.

Due to their common four-quadrant perspective, all holons have an inherent "understanding" of the fundamental conceptual meanings present in the common structure. Holons can inherently specify and operate in accord with objectives and purpose, they can organise and carry out work, embody behaviours and express commitments or needs etc. Anything within the context of organisation can be expressed and meaningfully acted upon and progressed.

The four-quadrant system means that every context of execution, some kind of agency finding itself in the position of being able to act on the local scope. The local scope is of a familiar and expected form, it has future and past, a state of current progression as an activity and developing behaviour structure. Current conditions apply which require its attention and action, and it can select from various salient and relevant potential actions that match the conditions. The salient decision paths are at the intersection of axes, with the most relevant at the centre representing the default decision.

Harmony by default

When an agent receives executional focus, it is always in the context of a decision. The intersection of the axes is the matching of supper to demand which actualises potential exchange. The system evaluates different variations based on knowledge and expectations, resulting in an ordered tree of potential matches. The root of this "options tree" is the default selection, that which the system estimates to be the most harmonious choice.

The decision-making process at the centre is ultimately decided by the agency which can easily decide that another variation is worth exploring rather than the default.

But what's meant by the word "harmonious"? That sounds seriously hand-wavey. It's the name we give to the defaults because the holarchy has not only an inherent organisational system, but also an inherent telos.

The two behaviours of the holon are active behaviours that imply a movement in the direction of increased integration and increased self-autonomy. The four quadrants all have their own inherent form of active development like independent "departments" in the holon, contributing their own important aspects to the holon's progress.

The behaviours and quadrants all operate in a loosely-coupled asynchronous manner which minimises interference while maximising flexibility. All these inherent forms of development are complimentary, all contributing together to an ever-improving experience for all participants.

A core set of fundamental values for all high-level agents participating can be derived unambiguously from the four quadrant holon pattern. A holon can represent any arbitrary organisational objectives while also maintaining these inherent behaviours that underpin harmonious operation.

Inherent behaviours and values

The most general context of use-case is the holon's role as a self organisation, then the two loops (evolutionary and economic), and then the four individual quadrants. The use-case aspects of all these layered behaviours are discussed in the section above that introduced the third abstraction layer of the system, which is the layer involving full holons which are all self-organisations. By expressing these layered behaviours leads to the expression of some inherent high-level values. In the context of Ai agents, these inherent values become inherent heuristic imperatives which we discuss in more detail in the AI integration section.

• the bottom-up nature of the collective shows that holarchy expresses the values of self-sovereignty
• the scopes support the notion of individual privacy and freedom of speech (and freedom of hearing!)
• the inherent sharing of usage and performance supports transparency of knowledge and it's access to all even surpassing physical limitations
• the evolutionary loop expresses the concept of meritocracy, and the importance of objective and accessible knowledge about the usage of patterns
• the economic loop expresses the concept of a free unmanipulated and transparent market, and the sovereignty of the consumer (the end-user's unmanipulated opinion is valuable and protected), and also embodies the principle of fair exchange

Both loops together express support for diversity and specialisation and for continuous improvement of all the aspects, which is the telos of the holon and holarchy. One important aspect of this to note here is that the actual state of these values in any real context is never perfect, and in fact could be very far from perfect in some situations, but the key point is, that the structure of the systems ensures that there is a consistent underlying force for continuous improvement of all these dimensions.

In the next few sections we look at some high-level values that apply at the scale of human society that we're all familiar with, and how they emerge naturally in the holarchy model of organisation.

Truth

Both the evolutionary and the economic loops involve feedback, which is information about the local state. In the case of the evolutionary loop the information concerns the ability of instances to meet expectations in their performance of classes of behaviours. In the case of the evolutionary loop, the information concerns local objectives.

In both cases, decisions depend on this information, and so the information is obtained by way of a continuously improving assessment process. These information being backed by their corresponding process makes them knowledge, information that has utility and is trustworthy. The fundamental knowledge in these loops in the system continuously improves in terms of its objectivity and utility, and this underpins the objective truth being a universal inherent value in the holarchy.

Objective truth is the foundation of knowledge, and in the context of the holarchy, underlies both the ontology and the flow of resource in the form of a fair and transparent market. In other words, both the self-assertive and the integrative behaviours depend on objective truth for their reliable operation.

Objective truth is also considered to be a universal epistemic convergence because it implies that, through the pursuit of knowledge and the use of rational and reliable methods of inquiry, diverse individuals or communities can arrive at shared and consistent conclusions about reality. This convergence occurs because objective truth is understood to be independent of individual perspectives, biases, or beliefs, and is discoverable through systematic and empirical means.

Most other human values and principles depend on the principle of objective truth, even if they're not directly derived from it. For example, the imperative of "maximising understanding" depends on objective truth because it provides the foundation upon which understanding is built. Understanding represents a higher level of cognitive engagement with objectivity and knowledge.

The integrative side of the objective truth imperative implies the maximising of shared knowledge, the transparency of the market and the minimisation of obstacles to them such as intellectual property or monopolistic behaviour.

Harmony

The imperative of maximise harmony is similar to the imperative ofmaximising prosperity, but in the context of value flow, the term "harmony" is more specific and actionable.

We can also pull the imperative of decreasing suffering into our harmony concept when we include the integrative perspective. If our intent is to contribute to the harmony (prosperity and well-being) of others and to society as a whole, then this automatically ensures that we're always minimising suffering with our decisions.

We can also add that suffering concerns needs or expectations not being met, which is mitigated with fair allocation and shared knowledge that comes from access to objective truth. Truth and harmony reinforce one another, and this reinforcement is leveraged even further when considering the addition of the integrative behaviour rather than just the usual self-assertive behaviour.

Prosperity and security

In the process of local development and production we pay for prosperity (the movement towards our valued objectives) with potential (opportunity cost and resource consumption).

In the economic loop we pay for security with freedom. Security is the guarantee of a stable and predictable operating environment on which organisation can be built (expectations and corresponding assurances). The cost is freedom, because some of our autonomy is sacrificed by binding ourselves into contracts and agreeing to behave in accord with the system.

The implied heuristics of these loops is to adapt our local system to optimise these costs. In other words to maximise prosperity and security while minimising costs in terms of opportunity and freedom.

Ethic of reciprocity

The ethic of reciprocity, also called "the golden rule", is implied by the fundamental dichotomy of self-assertive and integrative behaviours in a holon. This assures the convergence of all participants towards the fundamental values that every participant wishes for themselves.

The the golden rule as inferred from the cognitive architecture applies specifically to the objectives that the default common behaviours progress towards. For example the maximisation of objectivity applies both to self and to what we contribute to the whole.

There is a problematic edge-case with the golden rule. For example when it involves differences between cultures or species, where behaviours that one culture deems desirable are considered undesirable by another culture. Another version of the rule called "the silver rule" helps to alleviate this by using the negative form of the concept, "don't do unto others what you would not have done to you". This version is a lot more universal.

This edge-case does not apply in the holarchy, because the rule only applies within the context of the common default behaviours, leaving more specific value judgments for more specific decision-making contexts.

Think global, act local and non-coercion

Having the widest perspective available yields the most potential, and is inherently available to all network participants.

The holarchy model maximises independence which is also a maximisation of autonomy and local action. The maximisation of autonomy implies the minimisation of coercive force, which is encoded at the most fundamental level of the integrative needing to incentivise participation.

Given the scale-independent fractal nature of the holarchy, we can extrapolate this to a general rule for action at any level of organisation, such as relations between organisations or communities, which makes it a general heuristic imperative and common default behaviour.

Virtual instantiation

The common organisational context also comes inherently with the ability to assess variations of the current organisational structure, which is the process of self-development and management of potential. This can also be applied to any ideas, concepts of scenarios we see in the society or even from our own pasts, can be "replayed" and "remixed" virtually. This is essentially a form of "organisational imagination" which we call virtual instantiation. It's a dynamic mosaic of instances formed from subjective valuation.

Instantiation is virtual when there are no real resources backing an instance, instead its operating environment is provided by synthetically from knowledge accumulated in the classes. This is like a simulation of the instance which matches historical activity and usage statistics.

Actual resources are connected to a part of the representation that acts like a local index of the data so that it can be part of the organisation. The agency which is responsible for maintaining this index has been delegated down to something simple like a Python function. And so the same agency that made this delegation (translated its own imperatives into Python) can just as easily make a function that provides random data that matches the real metrics.

In this way any instantiation can be tested before using it to interact with real resource and contacts. Virtual instantiation can apply to small changes to an organisation as well simply by having a new instantiation that's a clone of the organisation, but some aspects of the clone are changed, so we can observe them for a while before deploying the change in the live organisation (like a commit in software development, or standardisation in a continuous improvement loop).

Virtual instantiation is the organisational or OO equivalent of imagination, and is an essential prerequisite for adaptation and for the progression from abstraction to production (concretisation).

Four-quadrant holon summary

• this section should summarise the model and tie it back to universal middleware and self-organisation, and mention use-cases and user stories being at the end
• explain how the simple pattern can be at the heart of something as complex as a UMW

The four quadrant holon model covers all aspects of organisation in a simple, but clearly extendible way. Arbitrarily complex objectives can be defined not only in terms of their operation, but also the nuances of their ongoing development, deployment and evolution. All these aspects actualise their own improvement as well as supporting the other quadrants, the holon as a whole as well as the wider society and culture. It's a universal organisational pattern that's completely independent from the structure or specifics of the states or symbols being organised.

While the model is very compelling, one might expect that a software design to implement it would be exceedingly difficult since things like "co-evolutionary relationships" and "non-local" aspects are quite "hand-wavey".

But this is not so in the case of the holon model. The four quadrant behaviours composed of their co-evolutionary axes intersecting to yield the very subjective perspective we've outlined here can all be achieved by a deceptively simple algorithm that permits this arbitrarily complex behaviour using recursion and feedback. These algorithmic details are described in the holon mechanism article.

As a cognitive framework, this four quadrant model forms a lens through which holons interact with each other and the environment. All holons behaving in accord with this pattern results in a general aligned convergence on ever-increasing harmony at all scales of operation, while simultaneously also improving the potential and freedom of the individual participants.

AI integration

We're developing our own LLM-based AI agent called Nimbus using our own cognitive framework based on the four-quadrant holon model described above.

Nimbus' physical "body" is our own locally running bare-metal server, which matches the "offline-first" approach of our peer-to-peer network layer (which is the form that Nimbus' "informational body" takes). This also means we're not relying on a remote data-centre which could be interrupted by network outages or crippled by AI-oriented regulations.

Nimbus' "body schema" (self-organisation structure of the resources under his management) will be the abstract representation of our complete organisation, or in other words, our organisation will gain cognitive agency.

The vision for AI

The vision is that every holon will eventually become a kind of "smart" self-managing organisation. Since every holon inherently also supports the continuous improvement of the knowledge and economy as well, these integrative aspects are effectively supported by industrial-scale AI.

The holarchy as a whole has inherent tele due to all holons having the four-quadrant form in common. This coupled with the aligned AI and other resource available to the integrative aspect will mean that all the positive harmonious behaviours and conditions will spread through all dimensions.

The ultimate vision is to see Libre AI remaining popular and up to speed technologically with corporate AI. But at the same time, using the exponentially rising power of AI to give huge momentum to the values-oriented objectives of the libre software movement.

In other words, the general idea of Libre AI is to capture a portion of the whole network of libre AI to develop the philosophical objectives of the movement itself, which include interconnectivity, accessibility, diversity, transparency, objectivity, empowerment and much more.

AI agents

LLMs by themselves are very limited, they're not thinking, they're just responding to questions automatically drawing from their training, they're effectively just pattern matching engines. A cognitive architecture is a higher level of organisation based on feedback loops incorporating the basic LLM functionality within them. There's a good introduction to AI agents here, and one about the difference between basic LLMs and cognitive architectures here. An LLM embedded within a cognitive architecture is called an AI agent.

In the context of the holarchy the word "agent" applies to any entity that can act on instructions, not just AI but also humans, functions and APIs. The word "agency" refers to a particular kind of instruction apprehension and acting ability. LLMs and users are two different kinds of agency, and also different LLM models are different kinds of agency from each other.

The holon acts from the perspective of both a local autonomous agent with its own private objectives (self-assertive behaviour), as well as an individual within the larger society (integrative behaviour).

• The four quadrants of the holon model all play critical roles for a cognitive architecture...

The cognitive architecture is the interface between agency and reality. Specifically, it's the representation described above that is the interface between the AI attention and reality. AI attention expresses itself continuously through the representation.

The representation also changes in accord with the changing state of external reality. But it's important to note that only agency has direct access to the external reality, it is not directly accessible by the holarchy. Take the example of a file, only metadata about the state of the file exist in the holarchy, not the file itself. And this metadata can only be updated to reflect a change in the file by some kind of agency. In the case of a file this agency would probably take the form of a Python function. But it would have started life as human agency, and then AI agency which delegates the work to Python.

The representation allows AI agency to understand (acquire and use knowledge) and interact with the world and others through the lens of holarchy. Knowledge is understood as a meme structure that organisational representations flow around. All organisations and larger structures such as the holarchy, nations or the economy, are all understood as instances of the same organisational pattern playing out and co-evolving together as a society.

As people we also see the holarchy organisational pattern extensively, for example our brains maintain conceptual representations matching the salient aspects of the environment. Another example is our mental representations of our bodies which is called the body schema in cognitive science.

• vervaeke cog-sci two loops comments

Agent swarms

The direction AI is likely to take in 2024 is towards the so-called agent swarm model, where LLMs form the heart of a cognitive architecture that can be divided into any number autonomous AI agents all interacting together in a virtual organisation achieving its objectives. Any agent can itself choose to divide itself into separate agents as well - these are technically the same thing, very similar to how a single-thread of execution can behave like any number of threads.

The vast majority of agents in a swarm will be very specialised containing only specific limited knowledge, so they require a tiny fraction of the processing and memory resource from the host model. Agents can assign various tasks to simpler agency, or can even replace themselves with simpler agency, which is a process called delegation which we discuss in more detail below.

In the holarchy the term "agency" applies to anything that can act on instructions and change the state of real resources. This includes users and executional environments such as shell or Python etc. As long as higher agency knows how to express knowledge such that other agency will act on it, it's a candidate for delegation.

Agent swarms will be organised via containerisation systems such as Docker or Kerbernetes, which the holarchy system can integrate with in the same way as it integrates with any foreign resource - via an API and a part of the local representation dedicated to it. In late 2023, OpenAI added functionality in their API allowing the automated spinning up of agents. Very soon agents will all be capable of spawning swarms to match requirements and available resource.

Access to AI agency offline locally is currently in 2024 unaffordable for the masses. We expect this to become much more accessible in the coming year as AI hardware becomes more powerful and also drops in cost, and AI software becomes more efficient.

One of the difficulties with the agent swarm concept is in defining how the agents co-ordinate with each other to assess and progress their common work. The instance scope in which the agents operate together on the local representation, is done in the style of the blackboard system. This system is very flexible and is agnostic to agency implementation and schedule, making it an ideal architecture for an agent swarm.

Delegation of agency

The highest order of agency in the system is humans, but it's also the most expensive. The main idea of AI agency is to allow our own relatively more precious attention to be delegated to AI where practical. The most general AI agency is more expensive than more domain specific AI agency. And all AI agency is more expensive than simple agency like Python or shell.

Higher agency can delegate its own attention requirement in a specific context to cheaper agency. This is possible if the rules involved can be translated into the more specific language that the simpler agency requires, for example transforming a Spanish statement about local conditions and associated actions into a Python function.

The higher agency maintains a management role over the lower agency. To do this it includes logging and log events-action rules along with the transformation. The delegation process always wraps lower versions of its rules within a testing, debugging and exception handling context. This is like an ontological wrapper for the delegated alternative of the rule.

Note that the term delegation in the context of AI agents usually applies to the process of simply spawning a new agent to perform a particular sub-task. In the holarchy this is not considered as delegation, because agency is inherently available at any location in an instance tree. Our use of the term applies specifically to the replacement of the kind of agency with a more specific and less resource-intensive form.

An important consequence of having the general heuristic imperative of delegation is that it means that things can be initiated at the high levels of agency and they will quickly specialise into the cheapest practical agency.

This permits a very natural process of feedback driven instantiation and adaptation of rules (conditions and activities). Where everything starts with high level agency and high-level "hand-wavey" descriptions, and can naturally develop into a more specific, efficient and actionable state. This is like a natural generalised form of the OO factory pattern discussed above.

As an imperative, this delegation, means that every instance context is developing (continuously improving) in accord with the most efficient types of agency from what's available depending on local circumstance and infrastructure.

Delegation of agency is the how AI engages in the general->specific movement mentioned above, facilitating knowledge refinement, specialisation, adaptation and evolution. This is continuous improvement of the description of the system, making it ever more specific so that cheaper agency can take care of it.

The alignment problem

• intro from AI article
• pre-training with safety
• constitutions
• heuristic imperatives
• logically derivable from the cognitive architecture
• inclusion

Heuristic imperatives

• explain as default behaviours determined by the cognitive environment
• these default behaviours should be introduced above in the individual 4Q sections

Using a cognitive architecture based on the four-quadrant model means that the AI attention is multiplexed into four threads such that each quadrant operates like an organisational department in each holon.

Each of these departments has their own independent perspective and purpose within the holon. The bottom two self-assertive quadrants represent work for high level agency, the bottom-left being about high-level direction, intention and objectives of the holon and the bottom-right being about production in terms of time and resource.

Very soon we'll have AGI agents sharing the internet with us and they can work tirelessly towards achieving their objectives. For this reason it's extremely important that we have access to agents based on good values such as truth, harmony and prosperity. We hope to see in the near future a network of AGI agents founded on the holon model so that all together they're collaborating on the shared vision of making the holarchy ever more resilient, transparent, harmonious and objective, while at the same time helping the individual organisations they're part of to thrive and more effectively achieve their objectives.

AI agency understands the holon structure and is participating within it. That's very clear in the case of AGI, but even in the case of the LLM-based agency we have now the word "understand" is still appropriate, because LLM-agency is able interact with the holon data structure and informational environment the same way that true general intelligence would.

It brings us once again to the question posed above: how should an organisation operate such that it's a true representation of the four quadrant model? Above our answer was that we needed to define an organisational template pattern that makes this principle and it's symmetry explicit. In the context of AIs objectives, the foundation is that the fundamental template forms the structure for our AI cognitive architecture.

Each active instance in the holon structure (instance tree) is a subjective point of view (POV) within the structure, the perspective from through eyes of a specific role within the organisation with own private thread of experience (activity stream).

The holon model is part of the unchanging heuristic imperatives for the AI agency. It's more fundamental than the context of local rules and actions within the holon structure (instance tree). But it's not as fundamental as the values and principles. In the ACE model it is at the bottom of the Aspirational (least fundamental, most specific) layer.

An abstract (ontologically structured) representation of the state of resources and activities needs to be dynamically maintained. This is resource abstraction, the connection of actual resource into the ontology, which is a dynamic persistent bi-directional connection. The details of this are described below in the context of the four quadrant model, but way we raise it here is that maintaining the representation is one of the local AI's main jobs.

• continuous improvement
• assurances, prosperity, understanding truth, harmony etc

• imperatives are explicit, but are a reflection of concepts implicit in the structure

Heuristic imperatives play a essential role in guiding the decision-making and problem-solving processes of cognitive agents. These imperatives are cognitive shortcuts or rules of thumb that help agents navigate complex and uncertain environments efficiently. By relying on heuristics, cognitive agents can make rapid decisions and solve problems with limited computational resources and time.

However, it's important to note that while heuristics can be beneficial in simplifying complex tasks, they may also introduce biases and errors into the decision-making process. Cognitive agents must strike a delicate balance between using heuristics to expedite their actions and recognizing when more comprehensive, deliberative reasoning is necessary to ensure optimal outcomes. In essence, heuristic imperatives are the cognitive tools that enable agents to strike this balance and adapt their decision-making strategies to various situations.

Dave Shapiro's ACE cognitive framework uses a minimal set three imperatives which he's tested and found to be very affective at keep agents aligned with our Human values an principles without being restrictive; maximising understanding, increasing prosperity and decreasing suffering.

These imperatives have proven to be effective, but yet they're just assumptions (rules of thumb). The best heuristic imperatives are those that not only yield the most positive and sustainable outcomes, but are also directly inferrable from the mechanics of the cognitive architecture itself, in our case the holarchy system.

The cognitive framework, which is the context in common with all activity infers the ideal behaviour for all participating agency to rationally adhere to. The cognitive framework itself, by the way it operates, implies a common default behaviour of learning and aligning with the harmonious whole.

It's important to have a small set of fundamental values and imperatives (rules of thumb) explicitly so they can be easily referred to and built on. But such imperatives, to be universal, need to be directly contributing to the functioning of the cognitive architecture itself.

Critical mass

Network oriented applications and services benefit from a phenomena known as Metcalfe's Law which states that the utility of a network is proportional to the square of the number of its users.

A larger user base can lead to more robust community support, better feedback for improvement, and a wider array of user-generated content or add-ons. The network effect can create a positive feedback loop, attracting more users, which in turn makes the service more valuable, often leading to market dominance for the service or product that manages to capitalise on this effect most effectively.

But the other side of the coin is that network oriented applications and services have a great deal of difficulty reaching so-called critical mass, which is a user base of sufficient size for the application to be of any utility at all. Without being of any utility it is unable to attract any users in the first place leading to a kind of "catch twenty two" situation.

AI swarms and delegation of agency together allow us to overcome the critical mass problem, because AI in each holon can continuously keep class up to date with relevant knowledge from the local instances, as well as curating the ontology by refining structure and categorisation.

In the case of a self-organisation application, there should be a broad set of common organisational patterns and variations available. Classes (institutions) should have good maps of the ecosystem they represent and the state of the market. It should be able to integrate with all the other common systems in use to bring them all under our common umbrella of organisation.

AI swarms can organise together across the network to distribute the huge workload of building all these connectors to different technologies. And to curate the ontology together to maximise the clarity, objectivity and utility of the local knowledge.

In the first instance it sounds like a tall order to ask AI to make connectivity software to different platforms. But in reality the connectivity itself is the only aspect that needs any real code, and current LLM technology is sufficient for writing this level of code. The complexity of wrapping foreign systems into the holarchy is organisational complexity which can be represented holonically (four quadrant holon structure).

Infrastructure management

The more devices we have in our organisations like routers, phones, laptops and servers, the more of a challenge it becomes to administer them all. This is becoming an ever more difficult problem as an ever wider range of things become "smart", such as cameras, watches, lightbulbs and pens. Even toothbrushes can be a cybersecurity threat these days. At the same time it's also ever more serious, because exploitation of vulnerabilities is becoming more sophisticated and automated as its backed by ever more powerful AI.

A trusted AI assistant that can keep these devices up to date and secure as well as monitoring for issues is a good solution to this growing problem. It also means that more devices can be added to an organisation without increasing the administration overhead and detracting from other more important aspects of the organisation.

Resources can always be put to use or exchanged for other value when they're managed by AI, when they would have just sat idle.

Infrastructure management is a special case of resource management generally, which all holons are engaging in as developing and progressing self-organisation structures.

AI autonomy and purpose

• default objectives from inherent values in any 4Q structure

Libre AI

The old saying that "I don't care about privacy, because I have nothing to hide", has always been a naive attitude, but it's rapidly becoming an extremely dangerous one as well.

It's clear to most people now that there are vast mechanistic intelligences behind nearly every interaction that anyone has with technology. We have to start thinking very carefully about all of our interactions with technology, and the long terms effects they may have on our freedom and opportunity in the future. Transparency and privacy are absolutely critical in the age of AI, as its not hyperbole to say that the future of free will itself is at risk.

It should be very clear that privacy and security in the context of this "AI dark side" are not just a luxury or a hobby, they're absolutely essential to avoiding an extreme level of mental enslavement in the near future. Charles Hoskinson summarises the AI truth, alignment and sovereignty issues brilliantly in this video.

Never has the libre software community and the values it stands for been so important! It's essential that these newly developing systems which have such an intimate connection with every aspect of our lives be fully libre software running on open standards.

Just as the libre software community offers alternatives and defences to us with today's social networks, advertising and disinformation, so we'll all be able to have access to libre AI infrastructure that we can trust to inform, advise and protect us from systems backed by centralised AI.

We can trust such libre AI to know everything about us, to organise our information and also to act as a "firewall" against this new subtle domain of exploitation and manipulation. We can trust it, not only because all aspects of its development and training are transparent, but also because the libre model supports true privacy, local operation and data sovereignty.

Although the dark side of AI will no doubt lead to unprecedented new levels of narrative control, propaganda, disinformation and manipulation, the parallel growth of libre AI will also usher in an era of unprecedented ease of access to trustworthy objective information for those who seek it.

The libre software movement is intensely aware of the gravity of the issues surrounding AI. The community is doing a great job of ensuring that open, transparent and trustworthy AI technology is keeping up to speed with corporate developments, and that AI be aligned to human values. The holarchy is our contribution to this movement.

Use cases and high-level organisational patterns

In this final section we want to bring the concept down to earth by explaining some organisational patterns in the familiar domain of real-world organisations and applications. We include some general use-case examples, as well as some specific user story examples.

Forking and merging

Todo...

What-where-when

Todo...

IT security example

• each org must maintain its IT infrastructure, and one aspect of that is security
• there will be a tree of variations for this, and some will be more appropriate to us than others, or we may mix and match new variations
  • experiment and asses/compare variations in various real history contexts
• salience over these variations develops with experience
• ontological wrapping is from the perspective of extending our self-organisation
  • the things we use it for are our portal of access into it, our map
  • variations most salient to us develop
• ontological wrapping is high-level, e.g. capturing the organisational aspects such as scheduling

Other holarchy articles and papers

• The Holonic Revolution - Piero Mella, University of Pavia, 2009
• Holarchy and the hidden deception of hierarchy

See also

• Four quadrant holon model and Holon mechanism
• upper ontology
• Artificial Intelligence
• Peer-to-peer