Chemical Organization Theory and Autopoiesis

E-mail communication of Francis Heylighen on 29 May 2018:

Inspired by the notion of autopoiesis (“self-production”) that Maturana and Varela developed as a definition of life, I wanted to generalize the underlying idea of cyclic processes to other ill-understood phenomena, such as mind, consciousness, social systems and ecosystems. The difference between these phenomena and the living organisms analysed by Maturana and Varela is that the former don’t have a clear boundary or closure that gives them a stable identity. Yet, they still exhibit this mechanism of “self-production” in which the components of the system are transformed into other components in such a way that the main components are eventually reconstituted.

This mechanism is neatly formalized in COT’s notion of “self-maintenance” of a network of reactions. I am not going to repeat this here but refer to my paper cited below. Instead, I’ll give a very simple example of such a circular, self-reproducing process:

A -> B,

B -> C,

C -> A

The components A, B, C are here continuously broken down but then reconstituted, so that the system rebuilds itself, and thus maintains an invariant identity within a flux of endless change.

A slightly more complex example:

A + X -> B + U

B + Y -> C + V

C + Z -> A + W

Here A, B, and C need the resources (inputs, or “food”) X, Y and Z to be reconstituted, while producing the waste products U, V, and W. This is more typical of an actual organism that needs inputs and outputs while still being “operationally” closed in its network of processes.

In more complex processes, several components are being simultaneously consumed and produced, but so that the overall mixture of components remains relatively invariant. In this case, the concentration of the components can vary the one relative to the other, so that the system never really returns to the same state, only to a state that is qualitatively equivalent (having the same components but in different amounts).

One more generalization is to allow the state of the system to also vary qualitatively: some components may (temporarily) disappear, while others are newly added. In this case, we  no longer have strict autopoiesis or [closure + self-maintenance], i.e. the criterion for being an “organization” in COT. However, we still have a form of continuity of the organization based on the circulation or recycling of the components.

An illustration would be the circulation of traffic in a city. Most vehicles move to different destinations within the city, but eventually come back to destinations they have visited before. However, occasionally vehicles leave the city that may or may not come back, while new vehicles enter the city that may or may not stay within. Thus, the distribution of individual vehicles in the city changes quantitatively and qualitatively while remaining relatively continuous, as most vehicle-position pairs are “recycled” or reconstituted eventually. This is what I call circulation.

Most generally, what circulates are not physical things but what I have earlier called challenges. Challenges are phenomena or situations that incite some action. This action transforms the situation into a different situation. Alternative names for such phenomena could be stimuli (phenomena that stimulate an action or process), activations (phenomena that are are active, i.e. ready to incite action) or selections (phenomena singled out as being important, valuable or meaningful enough to deserve further processing). The term “selections” is the one used by Luhmann in his autopoietic model of social systems as circulating communications.

I have previously analysed distributed intelligence (and more generally any process of self-organization or evolution) as the propagation of challenges: one challenge produces one or more other challenges,  which in turn produce further challenges, and so on. Circulation is a special form of propagation in which the initial challenges are recurrently reactivated, i.e. where the propagation path is circular, coming back to its origins.

This to me seems a better model of society than Luhmann’s autopoietic social systems. The reason is that proper autopoiesis does not really allow the system to evolve, as it needs to exactly rebuild all its components, without producing any new ones. With circulating challenges, the main structure of society is continuously rebuilt, thus ensuring the continuity of its organization, however while allowing gradual changes in which old challenges (distinctions, norms, values…) dissipate and new ones are introduced.

Another application of circulating challenges are ecosystems. Different species and their products (such as CO2, water, organic material, minerals, etc.) are constantly recycled, as the one is consumed in order to produce the other, but most are eventually reconstituted. Yet, not everything is reproduced: some species may become extinct, while new species invade the ecosystem. Thus the ecosystem undergoes constant evolution, while being relatively stable and resilient against perturbations.

Perhaps the most interesting application of this concept of circulation is consciousness. The “hard problem” of consciousness asks why information processing in the brain does not just function automatically or unconsciously, the way we automatically pull back our hand from a hot surface, before we even have become conscious of the pain of burning. The “global workspace” theory of consciousness says that various subconscious stimuli enter the global workspace in the brain (a crossroad of neural connections in the prefrontal cortext), but that only a few are sufficiently amplified to win the competition for workspace domination. The winners are characterized by much stronger activation and their ability to be “broadcasted” to all brain modules (instead of remaining restricted to specialized modules functioning subconsciously). These brain modules can then each add their own specific interpretation to the “conscious” thought.

In my interpretation, reaching the level of activation necessary to “flood” the global workspace means that activation does not just propagate from neuron to neuron, but starts to circulate so that a large array of neurons in the workspace are constantly reactivated. This circulation keeps the signal alive long enough for the different specialized brain modules to process it, and add their own inferences to it. Normally, activation cannot stay in place, because of neuronal fatigue: an excited neuron must pass on its “action potential” to connected neurons, it cannot maintain activation. To maintain an activation pattern (representing a challenge) long enough so that it can be examined and processed by disparate modules that pattern must be stabilized by circulation.

But circulation, as noted, does not imply invariance or permanence, merely a relative stability or continuity that undergoes transformations by incoming stimuli or on-going processing. This seems to be the essence of consciousness: on the one hand, the content of our consciousness is constantly changing (the “stream of consciousness”), on the other hand that content must endure sufficiently long for specialized brain processes to consider and process it, putting part of it in episodic memory, evaluating part of it in terms of its importance, deciding to turn part of it into action, or dismissing or vetoing part of it as inappropriate.

This relative stability enables reflection, i.e. considering different options implied by the conscious content, and deciding which ones to follow up, and which ones to ignore. This ability to choose is the essence of “free will“. Subconscious processes, on the other hand, just flow automatically and linearly from beginning to end, so that there is no occasion to interrupt the flow and decide to go somewhere else. It is because the flow circulates and returns that the occasion is created to interrupt it after some aspects of that flow have been processed and found to be misdirected.

To make this idea of repetition with changes more concrete, I wish to present a kind of “delayed echo” technique used in music. One of the best implementation is Frippertronics, invented by avant-garde rock guitarist Robert Fripp (of King Crimson): https://en.wikipedia.org/wiki/Frippertronics

The basic implementation consist of an analogue magnetic tape on which the sounds produced by a musician are recorded. However, after having passed the recording head of the tape recorder, the tape continues moving until it is read by another head that reads and plays the recorded sound. Thus, the sound recorded at time t is played back at time t + T, where the interval T depends on the distance between the recording and playback heads. But while the recorded sound in played back, the recording head continues recording all the sound, played by either the musician(s) or the playback head, on the same tape. Thus, the sound propagates from musician to recording head, from where is is transported by tape to the playback head, from where it is propagated in the form of a sound wave back to the recording head, thus forming a feedback loop.

If T is short, the effect is like an echo, where the initial sound is repeated a number of times until it fades away (under the assumption that the playback is slightly less loud than the original sound). For a longer T, the repeated sound may not be immediately recognized as a copy of what was recorded before given that many other sounds have been produced in the meantime. What makes the technique interesting is that while the recorded sounds are repeated, the musician each time adds another layer of sound to the layers already on the recording. This allows the musician to build up a complex, multilayered, “symphonic” sound, where s/he is being accompanied by her/his previous performance. The resulting music is repetitive, but not strictly so, since each newly added sound creates a new element, and these elements accumulate so that they can steer the composition in a wholly different direction.

This “tape loop” can be seen as a simplified (linear or one-dimensional) version of what I called circulation, where the looping or recycling maintains a continuity, while the gradual fading of earlier recordings and the addition of new sounds creates an endlessly evolving “stream” of sound. My hypothesis is that consciousness corresponds to a similar circulation of neural activation, with the different brain modules playing the role of the musicians that add new input to the circulating signal. A differences is probably that the removal of outdated input does not just happen by slow “fading” but by active inhibition, given that the workspace can only sustain a certain amount of circulating activation, so that strong new input tends to suppress weaker existing signals. This and the complexity of circulating in several directions of a network may explain why conscious content appears much more dynamic than repetitive music.

Chemical Organization Theory as a Modeling Tool

Heylighen, F., Beigi, S. and Veloz, T. . Chemical Organization Theory as a modeling framework for self-organization, autopoiesis and resilience . Paper to be submitted based on working paper 2015-01.

Introduction

Complex systems consist of many interacting elements that self-organize: coherent patterns of organization or form emerge from their interactions. There is a need of theoretical understanding of self-organization and adaptation: our mathematical and conceptual tools are limited for the description of emergence and interaction. The reductionist approach analyzes a system into its constituent static parts and their variable properties; the state of the system is determined by the values of these variable properties and processes are transitions between states; the different possible states determine an a priori predefined state-space; only after introducing all these static elements and setting up a set of conditions for the state-space can we study the evolution of the system in that state-space. This approach makes it difficult to understand a system property such as emergent behavior. Process metaphysics and action ontology assume that reality is not constituted from things but from processes or actions; the difficulty is to represent these processes in a precise, simple, and concrete way. This paper aims to formalize these processes as reaction networks of chemical organization theory; here the reactions are the fundamental elements, the processes are primary; states take the second place as the changing of the ingredients as the processes go on; the molecules are not static objects but raw materials that are produced and consumed by the reactions. COT is a process ontology; it can describe processes in any sphere and hence in scientific discipline; ‘.. method to define and construct organizations, i.e. self-sustaining networks of interactions within a larger network of potential interactions. .. suited to describe self-organization, autopoiesis, individuation, sustainability, resilience, and the emergence of complex, adaptive systems out of simpler components’ [p 2]. DPB: this reminds me of the landscape of Jobs; all the relevant aspects are there. It is hoped that this approach helps to answer the question: How does a system self-organize; how are complex wholes constructed out of simpler elements?

Reaction Networks

A reaction network consists of resources and reactions. The resources are distinguishable phenomena in some shared space, a reaction vessel, called the medium. The reactions are elementary processes that create or destroy resources. RN = <R,M>, where RM is a reaction network, R is a reaction, M is a resource: M = {a,b,c,…} and R is a subset of P(M) x P(M), where P is the power set (set of all subsets) of M and each reaction transforms a subset Input of M into a subset Output of M; the resources in I are the reactants and the resources in O are the products; I and O are multisets meaning that resources can occur more than once. R:x1+x2+x3+..→y1+y2+… The + in the left term means a conjunction of necessary resources x: if all are simultaneously present in I(r) then the reaction takes place and produces the products y.

Reaction Networks vs. Traditional Networks

The system <M,R> forms a network because the resources in M are linked by the reactions in R transforming one resource into another. What is specific for COT is that a reaction represents the transform from a multiplicity of resources into another multiplicity of them: a set I transforms to a set O. DPB: this reminds me of category theory. My principal question at this point is whether the problem of where organization is produced is not relocated: first the question was how to tweak static object into self-organization, now it is which molecules in which quantities and combination to conjuncture to get them to produce other resources and showing patterns at it. In RN theory the transform of resources can occur through a disjunction or a conjunction: the disjunction is represented by the juxtaposed reaction formulae, the conjunction by the + within a reaction formula.

Reaction Networks and Propositional Logic

Conjunction: AND: &; Disjunction: OR: new reaction line; Implication: FOLLOWS: →; Negation: NOT: -. For instance: a&b&c&..x. But the resources at the I side are not destroyed by the process then formally a&b&..→a&b&x&… Logic is static because no propositions are destroyed: new implications can be found, but nothing new is created. Negation can be thought of as the production of the absence of a resource: a+bc+ d = ac+ d – b. I and O can be empty and a resource can be created from nothing (affirmation, a) or a resource can create nothing (elimination, aor →-a). Another example is aa and hence a+(-a) = a-aand a-a: the idea is that a particle and its anti-particle annihilate one another, but they can be created together from nothing.

Competition and cooperation

The concept of negative resources allow the expression of conflict, contradiction or inhibition: a→-b what is the same as a+b0 (empty set): the more of a produced, the less of b is present: the causal relation is negative. The relation “a inhibits b” holds if: : a is required to consume but not produce b. The opposite “a promotes b” means that a is required to produce but not to consume b. When the inhibiting and promoting relations are symmetrical, a and b inhibit (a and b competitors) or promote (a and b cooperators) each other, but they do not need to be. Inhibition is a negative causality and promotion is a positive influence. If only positive influences or an even number of negative influences are included in a cycle then negative feedback occurs. When the number of negative influences is uneven then a positive feedback occurs. Negative feedback leads to stabilization or oscillation, positive feedback leads to exponential growth. In a social network a particular message can be promoted, suppressed or inhibited by another. Interaction sin the network occur through their shared resources.

Organizations

In COT and organization is defined as a self-sustaining reaction system: produced and consumed resources are the same: ‘This means that although the system is intrinsically dynamic or process-based, constantly creating or destroying its own components, the complete set of its components (resources) remains invariant, because what disappears in one reaction is recreated by another on, while no qualitatively new components are added’ [p 8]. DPB: I find this an appealing idea. But I find it also hard to think of the basic components that would make up a particular memeplex, even using the connotations. What in other words would the resources have to be and what the reactions to construct a memeplex from them? If the resource is an idea then one idea leads to another, which matches my theory. But this method would have to cater for reinforcement: and the idea itself does not much change, it does get reinforced as it is repeated. And in addition how would the connotation be attached to them: or must it be seen as an ‘envelope’ that contains the address &c, and that ‘arms’ the connoted idea (meme) to react (compare) with others such that the ranking order in the mind of the person is established? And such that stable network of memes is established such that they form a memeplex. The property of organization above, is central to the theory of autopoiesis, but, as stated in the text, without the boundary of a living system. But I don’t agree with this: the RC church has a very strong boundary that separates it from everything that is not the RC church. And so the RN model should cater for more complexity than only the forming of molecules (‘prior to the first cell’). The organization of a subRN <M’,R> of a larger RN <M,R> is defined by these characteristics: 1. closure: when I(r) is a part of M’ then O(r) is a part of M’ for all resources 2. semi-self-maintenance: no existing resource is removed, each resource consumed by some reaction is produced again by some other reaction working on the same starting set and 3. self-maintenance: each consumed resource x element of M’ is produced by some reaction in <M’,R> in at least the same amount as the amount consumed (this is a difficult one, because a ledger is required over the existence of the system to account for the quantities of each resource). ‘We are now able to define the crucial concept of organization: a subset of resources and reactions <M’,R> is an organization when it is closed and self-maintaining. This basically means that while the reactions in R are processing the resources in set M’, they leave the set M’ invariant: no resources are added (closure) and no resources are removed (Self-maintenance)’( emphasis of the author) [p 9]. The difference with other models is that the basic assumption is that everything changes, but this concept of organization means that stability can arise while everything changes continually, in fact this is the definition of autopoiesis.

Some examples

If a resource appears in both the I and the O then it is a catalyst.

Extending the model

A quantitative shortcoming, a possible extension, is the absence of relative proportions and of the relative speeds of the reactions. To extend quantitatively the model can be detailed to encompass all the processes that make up some particular ecology of reactions.

Self-organization

If we apply the rules for closure and maintenance we can know how organization emerges. If a reaction is added, a source for some resource is added which interrupts closure, or a sink is added which interrupts the self-maintenance. In general a starting set of resources will not be closed; their reactions will lead to new resources and so on; but the production of new ones will stop if no new resources are possible given the resources in the system; at that point closure is reached: ‘Thus, closure can be seen as an attractor of the dynamics defined by resource addition: it is the end point of the evolution, where further evolution stops’ [p 12]. In regards to self-maintenance, starting at the closed set, some of the resources will be consumed but not produced in sufficient amounts to replace the used amounts; these will disappear from the set; this does not affect closure because loss of resources cannot add new resources; resources now start to disappear one by one from the set; this process stops when the remaining resources only depend on the remaining ones (and not the disappeared ones): ‘Thus, self-maintenance too can be seen as an attractor of the dynamics defined by resource removal. The combination of resource addition ending in closure followed by resource removal ending in self-maintenance produces an invariant set of resources and reactions. This unchanging reaction network is by definition an organization’ [p 12]. Every dynamic system will end up in a attractor, namely a stationary regime that the system cannot leave: ‘In the attractor regime the different components of the system have mutually adapted, in the sense that the one no longer threatens to extinguish the other they have co-evolved to a “symbiotic”state, where they either peacefully live next to each other, or actively help one another to be produced, thus sustaining their overall interaction’ [p 12]. DPB: from the push and pull of these different attractors emerges (or is selected) an attractor that manages the behavior of the system.

Sustainability and resilience

An organization in the above sense is by definition self-maintaining and therefore sustainable. Many organizations grow because they produce more resources than they consume (e.g. positive feedback of resources: overproduced). Sustainability means the ability of an organization to grow without outside interference. Resilience means the ability to maintain the essential organization in the face of outside disturbances; a disturbance can be represented by the injection or the removal of a resource that reacts with others in the system. Processes of control are: buffering, negative feedback, feedforward (neutralizing the disturbance before it has taken effect). The larger the variety of controls the systems sports, the more disturbances it can handle, an implementation of Asby’s law of requisite variety. Arbitrary networks of reactions will self-organize to produce sustainable organizations, because an organization is an attractor of their dynamics. DPB: this attractor issue and bearing in mind the difficulties with change management, this reminds me of the text about the limited room an attracted system takes up in state-space (containment) explains why a system once it is ‘attracted’ it will not change to another state without an effort of galactic proportions. ‘However, evolutionary reasoning shows that resilient outcomes are more likely in the long run than fragile ones. First, any evolutionary process starts from some arbitrary point in the state space of the system, while eventually reaching some attractor region within that space. Attractors are surrounded by basins, from which all states lead into the attractor (Heylighen, 2001). The larger the basin of an attractor, the larger the probability that the starting point is in that basin. Therefore, the system is more likely to end up in an attractor with a large basin than in one with a small basin. The larger the basin, the smaller the probability that a disturbance pushing the system out of its attractor would also push it out of the basin, and therefore the more resilient the organization corresponding to the attractor. Large basins normally represent stable systems characterized by negative feedback, since the deviation from the attractor is automatically counteracted by the descent back into the attractor. .. However, these unstable attractors will normally not survive long, as nearly any perturbation will push the system out of that attractor’s basin into the basin of a different attractor. . This very general, abstract reasoning makes it plausible that systems that are regularly perturbed will eventually settle down in a stable, resilient organization’ [p 15].

Metasystem transitions and topological structures

A metasystem transition = a major evolutionary transition = the emergence of a higher order organization from lower order organizations. COT can be understood in this way if an organization S (itself a system of elements, albeit organized) behaves like a resource of the catalyst type: invariant under reactions but it has an input of resources it consumes I(S) and an output of resources it produces O(S), resulting in this higher order reaction: I(S) + S S + O(S), assume that I(S) = {a,b} and O(S) = {c,d,e}, then this can be rewritten as a+b+S S+c+d+e. S itself constitutes of organized elements and it behaves like a black box processing some input to an output. If S is resilient it can even respond to changes in its input with a changed output. Now the design space of meta-systems can be widened to include catalyst resources of the type S, organizations that are self-maintaining and closed.

Concrete applications

It is possible to mix different kinds of resources; this enables the modeling of complex environments; this is likely to make the ensuing systems’ organizations more stable. ‘Like all living systems, the goal or intention of an organizatrion is to maintain and grow. To achieve this, it needs to produce the right actions for the right conditions (e.g. produce the right resource to neutralize a particular disturbance). This means that it implicitly contains a series of “condition-action rules” that play the role of the organization’s “knowledge”on how to act in its environment. The capability of selecting the right (sequence of) action(s) to solve a given problem constitutes the organization’s “intelligence”. To do this, it needs to perceive what is going on in its environment, i.e. to sense particular conditions (the presence or absence of certain resources) that are relevant to its goals. Thus, an organization can be seen as a rudimentary “intelligence” or “mind”’ [p 20]. DPB: I find this interesting because of the explanation of how such a model would work: the resources are the rules that the organization needs to sort out and to put in place at the right occasion.

Stigmergy as a universal Coordination Mechanism (II)

Heylighen, F. . Stigmergy as a universal coordination mechanism II: Varieties and Evolution . Cognitive Systems Research (Elsevier) 38 . pp. 50-59. 2016

Abstract

One application is cognition, which can be viewed as an interiorization of the individual stigmergy that helps an agent to a complex project by registering the state of the work in the trace, thus providing an external memory’[p 50]. DPB: I understand this as: according to this hypothesis, stigmergy exists prior to cognition; this means that natural but non-living processes use stigmergy on an external medium; once they are alive they are (in addition) capable of internalizing stigmergy, namely by internalizing the medium. The process of internalization of individual stigmergy is the same as (the development of?) cognition. This is another way of saying that the scope of a system changes so as to encompass the (previously external) medium on which the stigmergy takes place. The self-organization is now internalized. Cognition is now internalized. How does this view on the concept of cognition relate to the concept of individuation as a view on cognition?

1. Introduction

To bring some order to these phenomena, the present paper will develop a classification scheme for the different varieties of stigmergy. We will do this by defining fundamental dimensions or aspects, i.e. independent parameters along which stigmergic systems can vary. The fact that these aspects are continuous (“more or less”) rather than dichotomous (“present or absent”) may serve to remind us that the domain of stigmergic mechanisms is essentially connected: however different its instances may appear, it is not a collection of distinct classes, but a space of continuous variations on a single theme – the stimulation of actions by their prior results’ [p 50]. DPB: this reminds me of the landscape of Jobs: at the connection of the memes and the minds, there is a trace of the meme left on the brain and a trace of the brain is added to the meme, leaving the meme and the brain damaged. This means that from the viewpoint of the brain the memeplex is the medium and from the viewpoint of the meme the brain is the medium. The latter is more obvious to see: traces can be left in individuals’ brains. The former implies that changes are imposed on the memeplex; but the memeplex is represented by the expression of ideas in the real and in the mind; the real is an external medium, accessible through first order observations; the expression of the memeplex existing in the mind is an external medium, because it exists in other persons’ minds and in versions of the Self, both accessible through second-order observations. Back to the landscape: it is there anyhow, the difference in states is how the Jobs are connected and as a consequence how they are bounded and how they individuate.

2. Individual vs. collective stigmergy

Ants do not require a memory, because the present stage of the work is directly discernible by the same ant, and also by a different ant. Because they have no memory, the work can be continued by the same ant, but by another just as well.

3. Sematectonic vs. marker-based stigmergy

Sematectonic means that the results of the work itself are the traces that signify the input for the next ant and the next state (Wilson Sociobiology, 1975). Marker-based means that the stigmergic stimulation occurs through traces in the shape of markers such as pheromones left by other individuals (ants, termites!) before them, and not by traces of the work itself indicating a particular stage (Parunak, H.V.D., A survey of environments and mechanisms for human-human stigmergy, In Environments for multi-agent systems II (Weyns, Parunak, Michel (Eds.), 2006). Marker signals represent symbols, while sematectonic signals the concrete thing. But this is not straightforward: the territory boundary indicated with urine markers are an indication of the fact that there is an animal claiming this territory, while the urine contains additional information specific for that animal. To spread urine evenly around the claimed area and to interpret the information contained by it is useful for both the defender and the visitor in order to manage a potential conflict. And hence to reduce the uncertainties from the environment for both. The point is that the urine represents both information about the object and about the context.

4. Transient vs. persistent traces

We have conceptualized the medium as the passive component of the stigmergic system, which undergoes shaping by the actions, but does not participate in the activity itself’ (emphasis of the author) [p 52]. But a medium is bound to dissipate and decay, unless the information is actively maintained and reconstructed; without ongoing updates it will become obsolete, especially as the situation changes. No sharp distinction can be made between transient and persistent traces, they are the extremes of a continuum. A persistent trace does not require the simultaneous presence of the agent, while a purely transient trace does require their simultaneous presence. Synchronous stigmergy means to broadcast some signal, releasing information not directed at any one in particular. ‘A human example would be the self-organization of traffic, where drivers continuously react to the traffic conditions they perceive’ [p 53]. DPB: the gist of this example is that the behavior of the drivers is the signal: it is synchronous, not directed at anyone in particular, and it is sematectonic, because it represents the state of the system.

5. Quantitative vs. qualitative stigmergy

Quantitative stigmergy means that stronger conditions imply more forceful action to follow, or, in practical terms: the stronger conditions imply a higher probability of action. Qualitative stigmergy refers to conditions and actions that differ in kind rather than in degree: thís trace leads to thát action. There is no clear distinction of these two categories.

6. Extending the mind

Traditionally, cognition has been viewed as the processing of information inside the brain. More recent approaches, however, not that both the information and the processing often reside in the outside world (Clark, 1998; Dror & Harnad, 2008; Hollan, Hutchins & Kirsh 2000) – or what we have called the medium. .. Thus the human mind extends into the environment (Clark & Chalmers, 1998), “outsourcing” some of its functions to external support systems. .. In fact, our mental capabilities can be seen as an interiorization of what were initially stigmergic interactions with the environment’ (emphasis of the author) [p 54]. DPB: beetje brakke quote. This reminds me of the idea that a brain would not have been required if the environment was purely random. Just because it is not, and hence patterns can be cognized, it is relevant to avail of the instrument for just that: a brain embodying a set of condition-action rules to generate an action from the state of the environment sensed by it. Stigmergic activity lacks a memory: its state represents its memory as it reflects its every experience. But now the system is dependent on the contingencies of the part of the environment that is the medium: in order to detach itself from the uncertainties of the environment it internalizes memory and information processing.

7. The evolution of cooperation

In a stigmergic situation the defector does not weaken the cooperator: the cost of a trace is sunk.