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februari 15, 2004
Gershenson och Heylighen om självorganisation
I papret When Can we Call a System Self-organizing? försöker Carlos Gershenson och Francis Heylighen ge nödvändiga villkor när ett system kan sägas vara självorganiserat/-nde. Personligen tilltalas jag av deras approach med dess fokusering på aspekter och observatörer samt deras ontologiska resonemang.
Abstract:
We do not attempt to provide yet another definition of selforganization, but explore the conditions under which we can model a system as self-organizing. These involve the dynamics of entropy, and the purpose, aspects, and description level chosen by an observer. We show how, changing the level or "graining" of description, the same system can appear selforganizing or self-disorganizing. We discuss ontological issues we face when studying self-organizing systems, and analyse when designing and controlling artificial self-organizing systems is useful. We conclude that self-organization is a way of observing systems, not an absolute class of systems.
Här nedan följer lite citat som förklarar de olika nyckelbegreppen. Det finns även något mer matematiska förklaringar, men de har undvikits här nedan. Emfas är i originalet.
Nyckelbegreppet aspect exemplifieras på följande sätt:
The variables defined by the values (A, B), respectively (A', B'), represent two aspects of the same system, where the observer has focussed on different, independent properties. For example, a particle s state includes both its position in space and its momentum or velocity. A subsystem is defined as a physical part of a system, limited to some of its components. Similarly, an aspect system can be defined as a functional part of a system, limited to some of its properties or aspects.
Let us illustrate this with a typical ALife model: swarming behaviour. Groups of agents can be seen as subsystems of the swarm. The positions of all agents define one aspect system, while their velocities define another aspect system. Assume we start with non-moving agents scattered all over the simulated space. The position aspect is characterized by maximum entropy (agents can be anywhere in space), while the velocity aspect has minimum entrop y (all have the same zero velocity). According to typical swarming rules, the agents will start to move with varying speeds towards the centre of the swarm while mutually adjusting their velocities so as not to bump into each other. This means that their states become more concentrated in position space, but more diffuse in velocity space. In other words, entropy decreases for the positions, while increasing for the velocities. Depending on the aspect we consider, the swarm self-organizes or self-disorganizes!
Andra nyckelbegrepp är purpose (function) och observer:
We have to be aware that even in mathematical and physical models of self-organizing systems, it is the observer who ascribes properties, aspects, states, and prob abilities; and therefore entropy or order to the system. But organization is more than low entropy: it is structure that has a function or purpose. Stafford Beer noted a very important issue: what under some circumstances can be seen as organization, under others can be seen as disorder, depending on the purpose of the system. He illustrates this idea with the following example: When ice cream is taken from a freezer, and put at room temperature, we can say that the ice cream disorganizes, since it loses its purpose of having an icy consistency. But from a physical point of view, it becomes more ordered by achieving equilibrium with the room, as it had done with the freezer. Again, the purpose of the system is not an objective property of the system, but something set by an observer.
W. Ross Ashby noted decades ago the importance of the role of the observer in relation to self-organizing systems: "A substantial part of the theory of organization will be concerned with properties that are not intrinsic to the thing but are relational between observer and thing".
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Self-organization is a way of modelling systems, not a class of systems. This does not mean that there is no self-organization independently of the observer, but rather that self-organization is everywhere.
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We have said that any dynamical system, if observed properly, can be seen as self-organizing. But if we set a different purpose or description level, then any dynamical system can be self-disorganizing. An economy will not be seen as selforganizing if we look only at a short timescale, or if we look at the scale of only one small business. An ant colony will not be self-organizing if we describe only the global behaviour of the colony (e.g. as an element of an ecosystem), or if we only list the behaviours of individual ants. We have to remember that the description of selforganization is partially, but strongly, dependent on the observer.
Sedan diskuteras de ontologiska problemen i teorier om emergenta fenomen, dvs vad är det som egentligen finns:
We can distinguish two types of being: relative and absolute. The relative (rel-being) is experienced by an observer with a finite cognitive capacity. It therefore depends on her/his context, and is limited. Strictly speaking, every cognizer has a different rel-being of anything, since every cognizer has a different context. Theoretically, we can assume that there exists an absolute being (abs-being), which would be the real thing (Kant s Ding-an-sich), independent of the observer, which observers correlate to their rel-beings. We can observe any abs-being from an infinity of perspectives and describe an infinity of potential properties or aspects. Nevertheless, most rel-beings and contexts are similar, since they are inspired by the same abs-being seen by similar observers from a similar point of view. This enables us to share knowledge, but it is because of the different nuances in the different rel-beings and contexts that we fail to agree in every situation.
Om de kausala sambanden mellan de olika nivåerna i systemet säger man:
What we could say is that when we observe certain conditions in the lower level, we can expect to observe certain properties at a higher level, and vice versa. There is correlation, but not actual causation.
Om det nu är helt fritt att välja nivå att studera ett system, vilka kriterier ska man använda?
This leads us to what is probably the most fundamental problem. If we can describe a system using different levels, aspects, or representations, which is the one we should choose? As Prem suggests, the level should be the one where the prediction of the behaviour of the system is easiest; in other words, where we need least information to make predictions.
De tror (tack och lov) inte att denna självorganiserande princip kan lösa all världens problem.
Independently of the definition of self-organizing systems, if we see them as a perspective for studying systems, we can use this perspective for designing, building, and controlling systems. A key characteristic of an artificial self-organizing system is that structure and function of the system "emerge" from interactions between the elements. The purpose should not be explicitly designed, programmed, or controlled. The components should interact freely with each other and with the environment, mutually adapting so as to reach an intrinsically "preferable" or "fit" configuration (attractor), thus defining the purpose of the system in an emergent way.
Certainly this is not the only approach for designing and controlling systems, and in many cases it is not appropriate. But it can be very useful in complex systems where the observer cannot a priori conceive of all possible configurations, purposes, or problems that the system may be confronted with. Examples of these are organizations (corporations, governments, communities), traffic control, proteomics, distributed robotics, allocation of ecologic resources, self-assembling nanotubes, and complex software systems, such as the semantic web.
Se även:
Carlos Gershenson. Se hans skrifter här , t.ex. hans thesis Artificial Societies of Intelligent Agents.
Francis Heylighen har skrivit en rad publikationer, t.ex. The Science of Self-organization and Adaptivity (PDF).
Heylighen är också redaktör för Principia Cybernetica Project där det finns många intressanta artiklar om självorganisation, cybernetik etc. Några exempel: Self-organization, Electronic Library med flera online böcker, t.ex. Claude Shannons A mathematical theory of communication (PDF), W. Ross Ashby An Introduction to Cybernetics. Det finns mycket intressant att läsa på denna sajt.
Läs också efterföljande blogganteckning om de två författarnas paper The Meaning of Self-organization in Computing (PDF) där beskriver sin vision hur man ska hantera den komplexa (komplicerade) värld som systemutveckling blivit. Se alltså Heylighen, Gershenson: The Meaning of Self-organization in Computing.
Posted by hakank at februari 15, 2004 07:37 EM Posted to Komplexitet/emergens