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Learning agents can improve performance cooperating with other agents, particularly learning agents forming a committee outperform individual agents. This "ensemble effect" is well known for multi-classifier systems in Machine Learning. However, multiclassifier systems assume all data is known to all classifiers while we focus on agents that learn from cases (examples) that are owned and stored individually. In this article we focus on how individual agents can engage in bargaining activitiesdoi:10.1145/1102351.1102431 dblp:conf/icml/OntanonP05 fatcat:syvyrnmnt5gh7jeabogblapjae