Reinforcement Learning

Welfare Maximization in Competitive Equilibrium: Reinforcement Learning for Markov Exchange Economy ICML 2022 What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator AAAI 2022 What Can We Learn Even from the Weakest? Learning Sketches for Programmatic Strategies AAAI 2022 When are Offline Two-Player Zero-Sum Markov Games Solvable? NeurIPS 2022 When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? ICLR 2022 When does return-conditioned supervised learning work for offline reinforcement learning? NeurIPS 2022 When Is Partially Observable Reinforcement Learning Not Scary? COLT 2022 When should agents explore? ICLR 2022 When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning NeurIPS 2022 When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning NeurIPS 2022 When to Update Your Model: Constrained Model-based Reinforcement Learning NeurIPS 2022 Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL ICLR 2022 Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error ICML 2022 Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters NeurIPS 2022 Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation ICLR 2022 X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learning UAI 2022 You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments NeurIPS 2022 You Only Live Once: Single-Life Reinforcement Learning NeurIPS 2022 Zero Experience Required: Plug & Play Modular Transfer Learning for Semantic Visual Navigation CVPR 2022 Zero-Shot Reward Specification via Grounded Natural Language ICML 2022 Abstraction-based branch and bound approach to Q-learning for hybrid optimal control L4DC 2021 Abstract Value Iteration for Hierarchical Reinforcement Learning AISTATS 2021 Accelerating Quadratic Optimization with Reinforcement Learning NeurIPS 2021 Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives NeurIPS 2021 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies ICML 2021