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Shaping multi-agent systems with gradient reinforcement learning

Olivier Buffet, Alain Dutech, François Charpillet
2007 Autonomous Agents and Multi-Agent Systems  
A définir par la commande Ö ×ÙÑ ßººº ABSTRACT. An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task of automatically building a coordinated system is of crucial importance. To that end, we design simple reactive agents in a decentralized way as independent learners. But to cope with the difficulties inherent to RL used in that framework, we have developed an incremental
more » ... earning algorithm where agents face a sequence of progressively more complex tasks. We illustrate this general framework by computer experiments where agents have to coordinate to reach a global goal. MOTS-CLÉS : A définir par la commande ÑÓØ×Ð ×ߺºº
doi:10.1007/s10458-006-9010-5 fatcat:7pdttndjyzhtrelvedbrh5y4o4