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Boosted and reward-regularized classification for apprenticeship learning., , and . AAMAS, page 1249-1256. IFAAMAS/ACM, (2014)Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards., , , , , , , , , and . CoRR, (2017)Learning from Demonstrations for Real World Reinforcement Learning., , , , , , , , , and 2 other author(s). CoRR, (2017)The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning, , , , , and . ICLR, (2017)cite arxiv:1704.04651.Rainbow: Combining Improvements in Deep Reinforcement Learning, , , , , , , , , and . (2017)cite arxiv:1710.02298Comment: Under review as a conference paper at AAAI 2018.Geometric Entropic Exploration., , , , , , , , , and . CoRR, (2021)Rainbow: Combining Improvements in Deep Reinforcement Learning., , , , , , , , , and . AAAI, page 3215-3222. AAAI Press, (2018)Boosted Bellman Residual Minimization Handling Expert Demonstrations., , and . ECML/PKDD (2), volume 8725 of Lecture Notes in Computer Science, page 549-564. Springer, (2014)Neural Predictive Belief Representations., , , , , and . CoRR, (2018)BYOL works even without batch statistics., , , , , , , , , and 1 other author(s). CoRR, (2020)