Reinforcement Learning

Towards Deployment-Efficient Reinforcement Learning: Lower Bound and Optimality ICLR 2022 TRAIL: Near-Optimal Imitation Learning with Suboptimal Data ICLR 2022 Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design ICLR 2022 Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing NeurIPS 2022 Truly Deterministic Policy Optimization NeurIPS 2022 Understanding Domain Randomization for Sim-to-real Transfer ICLR 2022 Understanding the Evolution of Linear Regions in Deep Reinforcement Learning NeurIPS 2022 Universally Expressive Communication in Multi-Agent Reinforcement Learning NeurIPS 2022 Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NeurIPS 2022 Unsupervised Skill Discovery via Recurrent Skill Training NeurIPS 2022 Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning ICLR 2022 Variational oracle guiding for reinforcement learning ICLR 2022 When should agents explore? ICLR 2022 When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning NeurIPS 2022 You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments NeurIPS 2022 Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives NeurIPS 2021 Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks AAAI 2021 Adapting to Reward Progressivity via Spectral Reinforcement Learning ICLR 2021 Adaptive Information Seeking for Open-Domain Question Answering EMNLP 2021 Adaptive Procedural Task Generation for Hard-Exploration Problems ICLR 2021 Addressing Action Oscillations through Learning Policy Inertia AAAI 2021 Adversarially Guided Actor-Critic ICLR 2021 ALFWorld: Aligning Text and Embodied Environments for Interactive Learning ICLR 2021 A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints AAAI 2021 Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning ICLR 2021