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Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning

Yang, Xintong ORCID: https://orcid.org/0000-0002-7612-614X, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Wu, Jing ORCID: https://orcid.org/0000-0001-5123-9861 and Lai, Yukun ORCID: https://orcid.org/0000-0002-2094-5680 2022. Abstract demonstrations and adaptive exploration for efficient and stable multi-step sparse reward reinforcement learning. Presented at: 27th IEEE International Conference on Automation and Computing (ICAC2022), 1-3 September 2022.

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Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Engineering
Computer Science & Informatics
Date of First Compliant Deposit: 27 July 2022
Last Modified: 10 Nov 2022 11:42
URI: https://orca.cardiff.ac.uk/id/eprint/151519

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