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Rainbow: Combining Improvements in Deep Reinforcement Learning

, , , , , , , , , and . (2017)cite arxiv:1710.02298Comment: Under review as a conference paper at AAAI 2018.

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Temporally-Extended ε-Greedy Exploration., , and . ICLR, OpenReview.net, (2021)An Analysis of Quantile Temporal-Difference Learning., , , , , , , , and . CoRR, (2023)Recurrent Experience Replay in Distributed Reinforcement Learning., , , , and . ICLR (Poster), OpenReview.net, (2019)The Phenomenon of Policy Churn., , , and . NeurIPS, (2022)Increasing the Action Gap: New Operators for Reinforcement Learning., , , , and . AAAI, page 1476-1483. AAAI Press, (2016)An Empirical Study of Implicit Regularization in Deep Offline RL., , , , , , , and . CoRR, (2022)Return-based Scaling: Yet Another Normalisation Trick for Deep RL., , , and . CoRR, (2021)Hybrid computing using a neural network with dynamic external memory, , , , , , , , , and 10 other author(s). Nature, 538 (7626): 471--476 (October 2016)Implicit Quantile Networks for Distributional Reinforcement Learning., , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 1104-1113. PMLR, (2018)Increasing the Action Gap: New Operators for Reinforcement Learning., , , , and . CoRR, (2015)