from Vitorino Ramos, On the Implicit and on the Artificial - Morphogenesis and Emergent Aesthetics in Autonomous Collective Systems, in ARCHITOPIA Book / Catalogue, Art, Architecture and Science, J.L. Maubant and L. Moura (Eds.), pp. 25-57, Minist�rio da Ci�ncia e Tecnologia, Feb. 2002
...Synergy is a ubiquitous phenomenon in nature and human societies alike. One well know example is provided by the emergence of self-organization in social insects, via direct (mandibular, antennation, chemical or visual contact, etc) or indirect interactions. The latter types are more subtle and defined by Grass� as stigmergy to explain task coordination and regulation in the context of nest reconstruction in Macrotermes termites. An example, could be provided by two individuals, who interact indirectly when one of them modifies the environment and the other responds to the new environment at a later time. In other words, stigmergy could be defined as a typical case of environmental synergy. Grass� showed that the coordination and regulation of building activities do not depend on the workers themselves but are mainly achieved by the nest structure: a stimulating configuration triggers the response of a termite worker, transforming the configuration into another configuration that may trigger in turn another (possibly different) action performed by the same termite or any other worker in the colony. Another illustration of how stigmergy and self-organization can be combined into more subtle adaptive behaviors is recruitment in social insects. Self-organized trail laying by individual ants is a way of modifying the environment to communicate with nest mates that follow such trails. It appears that task performance by some workers decreases the need for more task performance: for instance, nest cleaning by some workers reduces the need for nest cleaning. Therefore, nest mates communicate to other nest mates by modifying the environment (cleaning the nest), and nest mates respond to the modified environment (by not engaging in nest cleaning); that is stigmergy...
...Th�raulaz and Bonabeau described for instance, a model of nest building in wasps, in which wasp-like agents are stimulated to deposit bricks when they encounter specific configurations of bricks: depositing a brick modifies the environment and hence the stimulatory field of other agents. These asynchronous automata (designed by an ensemble of algorithms) move in a 3D discrete space and behave locally in space and time on a pure stimulus-response basis. There are other types of examples (e.g. prey collectively transport), yet stimergy is also present: ants change the perceived environment of other ants (their cognitive map, according to Chialvo and Millonas), and in every example, the environment serves as medium of communication.
What all these examples have in common is that they show how stigmergy can easily be made operational. As mentioned by Bonabeau, that is a promising first step to design groups of artificial agents which solve problems: replacing coordination (and possible some hierarchy) through direct communications by indirect interactions is appealing if one wishes to design simple agents and reduce communication among agents. Another feature shared by several of the examples is incremental construction: for instance, termites make use of what other termites have constructed to contribute their own piece. In the context of optimization (though not used on the present works), incremental improvement is widely used: a new solution is constructed from previous solutions (see ACO paradigm, Dorigo et al). Finally, stigmergy is often associated with flexibility: when the environment changes because of an external perturbation, the insects respond appropriately to that perturbation, as if it were a modification of the environment caused by the colony�s activities. In other words, the colony can collectively respond to the perturbation with individuals exhibiting the same behavior. When it comes to artificial agents, this type of flexibility is priceless: it means that the agents can respond to a perturbation without being reprogrammed in its intrinsic features to deal with that particular instability. The system organizes itself in order to deal with new object classes (conceptual ideas translated to the computer in the form of basic 2D/3D forms), or even new sub-classes. This task can be performed in real time, and in robust ways due to system�s redundancy...
...Synergy is a ubiquitous phenomenon in nature and human societies alike. One well know example is provided by the emergence of self-organization in social insects, via direct (mandibular, antennation, chemical or visual contact, etc) or indirect interactions. The latter types are more subtle and defined by Grass� as stigmergy to explain task coordination and regulation in the context of nest reconstruction in Macrotermes termites. An example, could be provided by two individuals, who interact indirectly when one of them modifies the environment and the other responds to the new environment at a later time. In other words, stigmergy could be defined as a typical case of environmental synergy. Grass� showed that the coordination and regulation of building activities do not depend on the workers themselves but are mainly achieved by the nest structure: a stimulating configuration triggers the response of a termite worker, transforming the configuration into another configuration that may trigger in turn another (possibly different) action performed by the same termite or any other worker in the colony. Another illustration of how stigmergy and self-organization can be combined into more subtle adaptive behaviors is recruitment in social insects. Self-organized trail laying by individual ants is a way of modifying the environment to communicate with nest mates that follow such trails. It appears that task performance by some workers decreases the need for more task performance: for instance, nest cleaning by some workers reduces the need for nest cleaning. Therefore, nest mates communicate to other nest mates by modifying the environment (cleaning the nest), and nest mates respond to the modified environment (by not engaging in nest cleaning); that is stigmergy...
...Th�raulaz and Bonabeau described for instance, a model of nest building in wasps, in which wasp-like agents are stimulated to deposit bricks when they encounter specific configurations of bricks: depositing a brick modifies the environment and hence the stimulatory field of other agents. These asynchronous automata (designed by an ensemble of algorithms) move in a 3D discrete space and behave locally in space and time on a pure stimulus-response basis. There are other types of examples (e.g. prey collectively transport), yet stimergy is also present: ants change the perceived environment of other ants (their cognitive map, according to Chialvo and Millonas), and in every example, the environment serves as medium of communication.
What all these examples have in common is that they show how stigmergy can easily be made operational. As mentioned by Bonabeau, that is a promising first step to design groups of artificial agents which solve problems: replacing coordination (and possible some hierarchy) through direct communications by indirect interactions is appealing if one wishes to design simple agents and reduce communication among agents. Another feature shared by several of the examples is incremental construction: for instance, termites make use of what other termites have constructed to contribute their own piece. In the context of optimization (though not used on the present works), incremental improvement is widely used: a new solution is constructed from previous solutions (see ACO paradigm, Dorigo et al). Finally, stigmergy is often associated with flexibility: when the environment changes because of an external perturbation, the insects respond appropriately to that perturbation, as if it were a modification of the environment caused by the colony�s activities. In other words, the colony can collectively respond to the perturbation with individuals exhibiting the same behavior. When it comes to artificial agents, this type of flexibility is priceless: it means that the agents can respond to a perturbation without being reprogrammed in its intrinsic features to deal with that particular instability. The system organizes itself in order to deal with new object classes (conceptual ideas translated to the computer in the form of basic 2D/3D forms), or even new sub-classes. This task can be performed in real time, and in robust ways due to system�s redundancy...
posted by choesnah at 6/30/2003 01:04:00 am
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