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Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2995-3003. PMLR, (2019)Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control With Action Constraints., , , , , and . IEEE Robotics Autom. Lett., 8 (8): 4449-4456 (2023)Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs., , , and . NeurIPS, (2022)Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice., , , , , , , , , and 5 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 17135-17175. PMLR, (2023)Leverage the Average: an Analysis of Regularization in RL., , , , , and . CoRR, (2020)Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning., , , , , and . NeurIPS, (2020)Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning., , , , and . NeurIPS, page 9828-9842. (2021)Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning., , , , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 3541-3552. PMLR, (2021)Avoiding Model Estimation in Robust Markov Decision Processes with a Generative Model., , , , and . CoRR, (2023)DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 33657-33673. PMLR, (2023)