In this paper, we propose the State Grouping scheme for coping with the problem of scaling up the Reinforcement Learning Algorithm to real, large size application. The grouping scheme is based on Geographical and trial-error information, and is made up with state generating, state combining, state Splitting, state forgetting procedures, with corresponding action selecting module and learning module.
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