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Controlling Complex Systems Dynamics without Prior Model

Boes, Jérémy and Gatto, François and Glize, Pierre and Migeon, Frédéric Controlling Complex Systems Dynamics without Prior Model. (2013) In: 5th International Conference on Agents and Artificial Intelligence (ICAART 2013), 15 February 2013 - 18 February 2013 (Barcelona, Spain).

(Document in English)

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Official URL: http://dx.doi.org/10.5220/0004243803890392


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.

Item Type:Conference or Workshop Item (Paper)
Additional Information:The original PDF is available at : http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0004243803890392
HAL Id:hal-01264526
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Deposited On:02 Dec 2015 14:54

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