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Shaping multi-agent systems with gradient reinforcement learning
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
doi:10.1007/s10458-006-9010-5
fatcat:7pdttndjyzhtrelvedbrh5y4o4