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Towards incremental social learning in optimization and multiagent systems
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08
Social learning is a mechanism that allows individuals to acquire knowledge from others without incurring the costs of acquiring it individually. Individuals that learn socially can thus spend their time and energy exploiting their knowledge or learning new things. In this paper, we adapt these ideas for their application to both optimization and multiagent learning. The approach consists of a growing population of agents that learn socially as they become part of the main population. We finddoi:10.1145/1388969.1389004 dblp:conf/gecco/OcaS08a fatcat:2k77bs3ivrdhpjpzkuz6earfhm