Four quadrant holon model

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Info.svg The purpose of this article is to serve as a software design pattern from which a peer can be programmed. While the Holarchy article introduced the general concepts and introduced the four quadrant model, this article goes into the data-structure and top-down/bottom-up processes that operate on it to form the foundation mechanics of the four quadrant model in practice.
  • The Holarchy article did not talk about the data structure, or the top-

down/bottom up aspects of the system.

  • Also the Holarchy article briefly introduced multiplexing from a high-level conceptual level, but this doc goes into the detail of it.

In the section we introduce a specific model in the form of a software design pattern for a p2p network peer that behaves as a holon, and as a network behaves as a holarchy. In the previous sections, we've introduced all the concepts involved in the holarchy design, and now in this section we combine all these concepts into a structure form that can be easily implemented in software.

The dichotomies of class and instance and of integrative and self-assertive combine to give us four definite roles that constitute the behaviour of a holon. By themselves the two dichotomies are too abstract to do anything, but the quadrant formed from their combination are specific enough to be defined and implementable.

Diagrammatically the upper quadrants represent the outward-facing integrative behaviours, the lower quadrants conversely represent that inward-facing self-assertive behaviours. The left and right quadrants represent the class (fixed rules) and instance (flexible strategies) respectively.

  • The top-left (TL) is the integrative class aspect, or what the class aspect is as a whole, which is the shared ontology.
  • The top-right (TR) is what the instance aspect is as a whole which is the market of resource in flux.
  • The bottom-left (BL) is the about the holon's own specific objectives.
  • The bottom-right (BR) concerns the holon's day-to-day operations.

The agent focus is multiplexed throughout the instance tree to yield separate private threads, all allocating their focus and other resource to their own activities and further child threads within. Each of the instance contexts is itself multiplexed into four, so that every holon is always allocating some resource to each of the fundamental quadrants of holon behaviour. Let's now go into more detail about each of these quadrants and dimensions.


In terms of executional flow, the top-down and bottom-up aspects of each axis set the stage for the order, so that the two TD sides of each axis' loop execute together and the BU sides of each axis' loop execute together. This is simply a logistical decision to minimise context shifting.

Class (L)

So far above we've described a class as a package of rules that are activated in response to specific local conditions. And that together, this package ecosystem as a whole forms a shared ontology of meaningful connections.

These rules are declarative in the sense that they refer only to their local environment in specifying their constituent conditions and actions. There is no information in rules that refers to the organisational system itself (control flow). This is important, because it means that rules can be represented entirely by domain-specific language and related class references (local scope namepsace).

  • timeless
  • classification; refining the ontology to model reality

Instance (R)

  • timeful, resource flow
  • instance as tree as well
  • instance tree is the holarchy - the actual instantiated organism like the singleton of life
  • continuous instiatiation

Instances are connected into time, they receive agent attention and have a specific state of information and resource. This specific state extends the general possibility space defined by the class. Instances have a history in the form of an activity stream, and a future in the form of schedule slots. Instances are threads of attention in which activity takes place in the present schedule slot (moment).

Integrative (T)

  • todo

In this interface role, the agency can express its heuristic imperative of accurately representing the real organisation, and presenting the representation so as to optimise the understanding, operation and direction of the organisation afforded to the participants.

We can think of the shared ontology and the market as being the fundamental "applications" of the holarchy, and AI as being the primary user interface for these applications. AI agency interacts with these applications on our behalf and presents the results to us in the most understandable way.

We mentioned above that the physical representation of a holon is its interface, but it's such a fundamental layer of functionality that the interface is more akin to an API that something a user would work with directly. So AI agency site between the basic organisational level and the user. The AI is also in a position to delegate its interface role down to a simpler form such as a browser DOM environment.

???These objects have continuous runtimes like API end-points, except that the services and capabilities that they advertise can be diverse and they have the common language of market and organisation in which to participate. The interfaces they present can vary over time, and come with market variables like reputation, supply and demand.

Self-assertive (B)

The bottom quadrants are both dedicated to the self-assertive behaviour of the holon. Together their purpose is to achieve the objectives of the organisation, and to ensure they using the most useful patterns and adapting them effectively towards their local needs.

Shared ontology (TL)

The ideal objective of this quadrant is perfection of the public shared ontology. The ontology is a shared map we all collaborate on and use to navigate and participate in society. We're all participatory members of the public ontology project. The ontology takes the form of the structure of established patterns of usage and the associated metrics that help with decision making and daily operations. Perfecting the ontology means transparently sharing aggregated usage statistics and performance metrics, and making our own knowledge and adaptations more understandable and usable.

Making shareable means ensuring the ontology accurately and completely reflects the true state of the organisation, and aggregating the most useful metrics in the context of the conditions they apply to. Although the sharing of knowledge primarily concerns packages of rules and their associated variations and metric, it's also about maintaining traditional sources of knowledge such as tutorials and knowledge-bases etc incorporated into the ontological map.

A class contains a map of its instances and their usage statistics. Classes have relations between them, the most fundamental being dependence. The conditions and the established paths of usage associated with them are the basis of the maps that guide attention into the specifics of its structure. The whole graph of classes together are the shared ontology. The ontology maps to the holarchy (the totality of all organisation-holon instances) just as culture is the abstract map of society.

The ontology is an organised structure of shared knowledge in the form of packaged of rules (classes) which, when instantiated, assess local conditions and activate relevant patterns in accord with them.

The purpose of knowledge is subjective local consumption and understandability. Understanding it means that an individual's behavioural patterns have been changed by the knowledge. We say the individual has embodied the knowledge, or in the case of an organisation-holon the knowledge has been instantiated in the organisation.

It's clear that knowledge, involving communication and understandability, must include the dynamics of community, not just the individual (community and communication are interdependent). In terms of networking, the sharing of knowledge is about the replication of classes to maintain a structured shared ontology of all knowledge.

It's the job of p2p to maintain the ontology, but the ontology as a whole is abstract, it can never be fully known by any individual holon. Individuals can only maintain a small portion of the whole based on their own interests, history and circumstances. But their contributions all overlap to create a unified whole in the abstract, and any peer can access any part of the ontology they wish to using easily followed maps.

We all want the best for society but it needs to be balanced with the self-assertive. A simple and natural foundation to this principle is that knowledge should be as transparent as practically possible. And it's a heuristic imperative to maximise this transparency.

The transparency of knowledge is not only about access to the informational aspect of the knowledge, it's about maximising the understandability of it. This calls for a common process by which knowledge is instantiated, and also by which the instantiation can be assessed. Knowledge can be more readily obtained and utilised if its performance under various conditions can be assessed.

  • knowledge can be used, but we must be able to assess the usage
  • sharing knowledge means sharing usage
  • tie in with libre software movement

Market (TR)

  • market is a distribution of supply and demand
  • but as a concept its interdependent with specialist knowledge (participatory, also fair and transparent)
  • balanced exchange (implies no usury and no charity)
  • evolving market
  • the flow of resource
  • the common logistic
  • contributing to the harmony of the stock and flow

The free market is a controversial topic and considered by many to be something entirely alien to nature. But it's important to note that it's not the market dynamic that's unnatural, it's centralised power. The free market dynamic, when transparent and unmanipulated, permits a harmonious balanced resource allocation system. The most fundamental systemic aspect of a biological organism is its bio-economic aspect. The market dynamic cannot achieve this harmonious potential alone, it needs to be balanced with the integrative behaviour of the shared ontology.

The ontology of classes determines how things are organised. The other side is what is being organised, the actualised instances of the classes in the ontology. This side is fundamentally about the specific state, connection and flow of resources and attention throughout the network. In terms of a dynamic system, this resource flow takes the form of a decentralised market, where matching supply and demand pairs represent potential for flow.

  • it's in terms of flow that we talk about actualised organisation

The instances containing one another form a structure of agency, resource and information. The resource structure is constantly in flux around form determined by the ontology. This is the same as molecules, proteins and cells that make up an organism being in flux around form determined by the organism's DNA. Likewise, our own cognitive symbols are in flux around forms within the collective unconscious.

An instance is a physical representation of a class which is composed of actual resource in a real state, and having a history and future. In OO terms, this representation is the public interface of the organisation. It's formed from resource which is native to the context it's instantiated within. This form is maintained by the implementation of the rules constituting the instantiated classes.

  • it's p2p so market is not some "place", it's really a protocol amongst individuals,
  • but the p2p aspects means we can all participate in it as if it were a place
  • the market is about presenting market variables such as our state of supply, demand

???The internal dynamic is not common to all, it's specific and involves subjective local objectives and values. It may even operate in accord with a different network topology. The way they operate depends entire on the preferences and conventions of the participants involved.

Organisation (BR)

As discussed above, a class is a package of declarative rules in the form of conditions and corresponding activities. The evaluation of the conditions has already been discussed because it's an integrative process. Here we turn to the performance of the activities which progress the holon towards its objectives.

Agency in the holon performs the queued activities resulting local change described by an activity stream. Activities are assigned to timeslots in a schedule so that agency can be organised into arbitrarily many threads of operation. In other words, the roles in the organisation all carry out their day-to-day operations in a local shared context together.

Activities occur in the context of an instantiated holon forming a tree of experiential threads. Activities are book in future time slots, the work the represent is performed in the present, and they end as a description in an activity stream.

  • operational
  • assistant
  • maintaining the representation
  • activity stream

Curation (BL)

We call this curation because it's all about improving the ontological structure and organisational state representation. Increasing its accuracy, maintaining it more efficiently, adapting it to better fit local needs, fine-tuning its objectives and so on.

AI plays another important role in the holarchy, which can be summed up as curation of the ontology. Refinement, diversification and assessment of the ontology. These are all things we've discussed above as important aspects of the holarchy protocol, but in reality these things require a level of commitment that we can't expect from users who don't have the spare time or motivation for this. AI allows the vast majority of curation work to be completely automated with just some general heuristic imperatives to guide it. Curation is a role that AI is perfectly suited for managing and delegating down to simpler agency in most cases. using this approach the local representations and ontology will be orders of magnitude richer than would be possible with human users alone.

  • on the biz - for the purpose of the biz
  • going back to the packages of rules and conditions
    • use pattern language as intro to rules-based organisation
  • on the biz is like package management
  • integration, usage statistics, reports, adaptation
  • classification
  • selection and key-changes

See also