SEAPoT-RL: Selective exploration algorithm for policy transfer in RL
We propose a new method for transferring a policy from a source task to a target task in model-based reinforcement learning. Our work is motivated by scenarios where a robotic agent operates in similar but challenging environments, such as hospital wards, differentiated by structural arrangements or...
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Main Authors: | , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2017
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Online Access: | https://ink.library.smu.edu.sg/sis_research/3762 https://ink.library.smu.edu.sg/context/sis_research/article/4764/viewcontent/14729_66712_1_PB.pdf |
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Institution: | Singapore Management University |
Language: | English |