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Controlling Complex Systems Dynamics without Prior Model

Jérémy Boes 1 François Gatto 1 Pierre Glize 1 Frédéric Migeon 1
1 IRIT-SMAC - Systèmes Multi-Agents Coopératifs
IRIT - Institut de recherche en informatique de Toulouse
Abstract : Controlling complex systems imposes to deal with high dynamics, non-linearity and multiple interdependencies. To handle these dif¿culties we can either build analytic models of the process to control, or enable the controller to learn how the process behaves. Adaptive Multi-Agent Systems (AMAS) are able to learn and adapt themselves to their environment thanks to the cooperative self-organization of their agents. A change in the organization of the agents results in a change of the emergent function. Thus we assume that AMAS are a good alternative for complex systems control, reuniting learning, adaptivity, robustness and genericity. The problem of control leads to a speci¿c architecture presented in this paper.
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  • HAL Id : hal-01264526, version 1
  • OATAO : 12389


Jérémy Boes, François Gatto, Pierre Glize, Frédéric Migeon. Controlling Complex Systems Dynamics without Prior Model. 5th International Conference on Agents and Artificial Intelligence (ICAART 2013), Feb 2013, Barcelona, Spain. pp. 1-4. ⟨hal-01264526⟩



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