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- W2500976893 abstract "In this paper, a novel autonomous learning framework is proposed. Different form the traditional learning framework, which maps environment to the action space directly, the new method abstracts behavior policies from the demonstrations and expresses it with a parameterized model. Based on the parameterized policies, cost function and environment constraints are generated, which together with the dynamic constraints of the robot are used to optimize the decision actions. A simulation on the grid world proved the effectiveness of the proposed method." @default.
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- W2500976893 date "2016-01-01" @default.
- W2500976893 modified "2023-10-17" @default.
- W2500976893 title "Autonomic Learning Framework Based on Behavior Policy" @default.
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- W2500976893 doi "https://doi.org/10.1007/978-981-10-0207-6_68" @default.
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