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Using a million cell simulation of the cerebellum: Network scaling and task generality.

, , , and . Neural Networks, (2013)

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Keep CALM and Explore: Language Models for Action Generation in Text-based Games., , , and . EMNLP (1), page 8736-8754. Association for Computational Linguistics, (2020)Graph Constrained Reinforcement Learning for Natural Language Action Spaces., and . ICLR, OpenReview.net, (2020)Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker., and . RoboCup, volume 6556 of Lecture Notes in Computer Science, page 254-265. Springer, (2010)Deep Reinforcement Learning in Parameterized Action Space., and . ICLR (Poster), (2016)Learning Calibratable Policies using Programmatic Style-Consistency., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 11001-11011. PMLR, (2020)MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control., , , , , and . NeurIPS, (2022)ALFWorld: Aligning Text and Embodied Environments for Interactive Learning., , , , , and . ICLR, OpenReview.net, (2021)Using a million cell simulation of the cerebellum: Network scaling and task generality., , , and . Neural Networks, (2013)Reading and Acting while Blindfolded: The Need for Semantics in Text Game Agents., , and . NAACL-HLT, page 3097-3102. Association for Computational Linguistics, (2021)Machine Learning Capabilities of a Simulated Cerebellum., , , and . IEEE Trans. Neural Networks Learn. Syst., 28 (3): 510-522 (2017)