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Helping an Agent Reach a Different Goal by Action Transfer in Reinforcement Learning

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posted on 2024-11-15, 22:52 authored by Yuchen Wang, Fenghui RenFenghui Ren, Minjie ZhangMinjie Zhang
© 2019, Springer Nature Switzerland AG. Reinforcement learning agents can be helped by the knowledge transferred from experienced agents. This paper studies the problem of how an experienced agent helps another agent learn when they have different learning goals by action transfer. This problem is motivated by the widely existing situations where agents have different learning goals and only action transfer is available to agents. To tackle the problem, we propose an approach to facilitate the transfer of actions that are right to a learning agent’s goal. Experimental results show the effectiveness of the proposed approach in transferring right actions to an agent and helping the agent learn to reach a different goal.

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Wang, Y., Ren, F. & Zhang, M. (2019). Helping an Agent Reach a Different Goal by Action Transfer in Reinforcement Learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11919 LNAI 15-27.

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English

RIS ID

140702

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