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Abstracting Reinforcement Learning Agents with Prior Knowledge.

, and . PRIMA, volume 11224 of Lecture Notes in Computer Science, page 431-439. Springer, (2018)

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Intrinsically Motivated Lifelong Exploration in Reinforcement Learning., and . JSAI, volume 1357 of Advances in Intelligent Systems and Computing, page 109-120. Springer, (2020)Goal-driven active learning., and . Auton. Agents Multi Agent Syst., 35 (2): 44 (2021)Towards Interpretable Reinforcement Learning with State Abstraction Driven by External Knowledge., and . IEICE Trans. Inf. Syst., 103-D (10): 2143-2153 (2020)Exploration via Progress-Driven Intrinsic Rewards., and . ICANN (2), volume 12397 of Lecture Notes in Computer Science, page 269-281. Springer, (2020)Towards High-Level Intrinsic Exploration in Reinforcement Learning., and . IJCAI, page 5186-5187. ijcai.org, (2020)Doctoral Consortium.Abstracting Reinforcement Learning Agents with Prior Knowledge., and . PRIMA, volume 11224 of Lecture Notes in Computer Science, page 431-439. Springer, (2018)Local Control is All You Need: Decentralizing and Coordinating Reinforcement Learning for Large-Scale Process Control., , and . SICE, page 468-474. IEEE, (2022)Goal-Driven Active Learning., and . AAMAS, page 1923-1925. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), (2022)Interpretable Imitation Learning with Symbolic Rewards., , and . ACM Trans. Intell. Syst. Technol., 15 (1): 4:1-4:34 (February 2024)Efficient Reinforcement Learning through Improved Cognitive Capabilities.. Graduate University for Advanced Studies, Japan, (2021)