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Learning locomotion skills using DeepRL: does the choice of action space matter?, and . Symposium on Computer Animation, page 12:1-12:13. Eurographics Association / ACM, (2017)Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow., , , , and . ICLR (Poster), OpenReview.net, (2019)Offline Meta-Reinforcement Learning with Advantage Weighting., , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 7780-7791. PMLR, (2021)MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies., , , , and . NeurIPS, page 3681-3692. (2019)SuperPADL: Scaling Language-Directed Physics-Based Control with Progressive Supervised Distillation., , , and . CoRR, (2024)Adversarial Motion Priors Make Good Substitutes for Complex Reward Functions., , , , , , and . IROS, page 25-32. IEEE, (2022)CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control., , , , , , , and . CoRR, (2024)RoboPianist: A Benchmark for High-Dimensional Robot Control., , , , , , , , , and . CoRR, (2023)Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control., , , , , and . Int. J. Robotics Res., 44 (5): 840-888 (2025)Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning., , , , , , , , , and 8 other author(s). CoRR, (January 2025)