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- W2358867982 abstract "We exert the profit-sharing reinforcement learning method into the semi-autonomous agent system,and compare it with the other reinforce learning method--Q-learning.Profit-sharing method is more robust and fit for the dynamic environment which includes many uncertain factors,especially in the partial MDPs(Markov Decision Processes) environment.Facing the semi -autonomous property of the agent,we propose an improving learning method of profit-sharing in the semi-autonomous agent system and test it in a combat simulation environment that finds the safety hidden space in battlefield.At last we contract and analyze these methods to the others." @default.
- W2358867982 created "2016-06-24" @default.
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- W2358867982 date "2007-01-01" @default.
- W2358867982 modified "2023-09-28" @default.
- W2358867982 title "Research of profit-sharing reinforcement learning method based on semi-autonomous agent" @default.
- W2358867982 hasPublicationYear "2007" @default.
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