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Application of reinforcement learning to control a multi-agent system

François Klein 1 Christine Bourjot 1 Vincent Chevrier 1 
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : This study takes place in the context of multi-agent systems (MAS), and especially reactive ones. In such a system, interactions are essential, and trigger a collective behaviour that is not directly linked to the individual ones. Whereas the evolution of the system is unknown if not tried, the regularity of emergent structures in the system is observable and forms a global behaviour. In this paper, we propose to control the global behaviour of a MAS thanks to reinforcement learning tools applied at its global level. We also highlight the choice of the features taken into account to achieve this control, that is the information considered to decide which action to perform.
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Submitted on : Monday, November 3, 2008 - 10:01:58 AM
Last modification on : Saturday, June 25, 2022 - 7:39:50 PM
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  • HAL Id : inria-00336173, version 1



François Klein, Christine Bourjot, Vincent Chevrier. Application of reinforcement learning to control a multi-agent system. International Conference on Agents and Artificial Intelligence - ICAART 09, Jan 2009, Porto, Portugal. ⟨inria-00336173⟩



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