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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)Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences., , , , , and . CoRR, (2021)Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints., , , , , and . CoRR, (2023)Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning., , and . CoRR, (2019)Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming., , and . CoRR, (2017)No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL., , , , , , , , , and . CoRR, (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)Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs., , , and . NeurIPS, (2022)Leverage the Average: an Analysis of Regularization in RL., , , , , and . CoRR, (2020)Multi-Agent Behavior Retrieval: Retrieval-Augmented Policy Training for Cooperative Manipulation by Mobile Robots., , and . CoRR, (2023)