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Apprentissage par Renforcement et Théorie des Jeux pour la coordination de Systèmes Multi-Agents

Alain Dutech 1 Raghav Aras 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This article presents the main reinforcement learning algorithms that aim at coordinating multi-agent systems by using tools and formalisms borrowed from Game Theory. Limits of these approaches are studied and discussed in order to draw some promising lines of research for that particular field. We argue more deeply around the central notions of Nash equilibrium and games with imperfect monitoring.
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https://hal.inria.fr/inria-00102192
Contributor : Alain Dutech <>
Submitted on : Friday, September 29, 2006 - 1:54:49 PM
Last modification on : Friday, February 26, 2021 - 3:28:04 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 1:17:34 AM

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Alain Dutech, Raghav Aras, François Charpillet. Apprentissage par Renforcement et Théorie des Jeux pour la coordination de Systèmes Multi-Agents. Colloque Africain sur la Recherche en Informatique - CARI 2006, 2006, Cotonou/Bénin. ⟨inria-00102192⟩

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