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

  • Yuchen WangEmail author
  • Fenghui Ren
  • Minjie Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11919)

Abstract

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.

Keywords

Different goals Action transfer Reinforcement learning 

Notes

Acknowledgement

This research is supported by a DECRA Project (DP140100007) from Australia Research Council (ARC), a UPA and an IPTA scholarships from University of Wollongong, Australia.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computing and Information TechnologyUniversity of WollongongWollongongAustralia

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