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An autonomous explore/exploit strategy
2005
Proceedings of the 2005 workshops on Genetic and evolutionary computation - GECCO '05
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance between exploring and exploiting changes as the training progresses due to the increasing amount of learnt knowledge. This shift in balance is not known a priori so an autonomous online adjustment is sought. Human beings manage this balance through logic and explorations based on feedback from the environment. The XCS
doi:10.1145/1102256.1102280
dblp:conf/gecco/McMahonSB05
fatcat:vuqkmebcmfgz3cqdhwq73rtkci