|Título||Cooperative Multiagent Learning|
|Publication Type||Journal Article|
|Year of Publication||2003|
|Authors||Plaza E, Ontañón S|
|Journal||Adaptative Agents and Multi-Agent Systems|
Cooperation and learning are two ways in which an agent can improve its performance. Cooperative Multiagent Learning is a framework to analyze the trade-off between cooperation and learning in multi agent systems. We focus on multiagent systems where individual agents are capable of solving problems and learning using CBR (Case-based Reasoning). We present several collaboration strategies for agents that learn and their empirical results in several experiments. Finally we analyze the collaboration strategies and their results along several dimensions, like number of agents, redundancy, CBR technique used, and individual decision policies.
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