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Grounding English Commands to Reward Functions., , , , , , , , and . Robotics: Science and Systems, (2015)Deep Reinforcement Learning from Policy-Dependent Human Feedback., , , and . CoRR, (2019)A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented Instructions., , , , , , and . RoboNLP@ACL, page 67-75. Association for Computational Linguistics, (2017)Social Contract AI: Aligning AI Assistants with Implicit Group Norms., , , , , , , , and . CoRR, (2023)Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction., and . NeurIPS, (2022)Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning., and . NeurIPS, (2022)Deciding What to Learn: A Rate-Distortion Approach., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 373-382. PMLR, (2021)Value Preserving State-Action Abstractions., , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 1639-1650. PMLR, (2020)State Abstraction as Compression in Apprenticeship Learning., , , , , and . AAAI, page 3134-3142. AAAI Press, (2019)State Abstractions for Lifelong Reinforcement Learning., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 10-19. PMLR, (2018)