Deep RL

Local-Guided Global: Paired Similarity Representation for Visual Reinforcement Learning CVPR 2023 Loosely consistent emphatic temporal-difference learning UAI 2023 Low Emission Building Control with Zero-Shot Reinforcement Learning AAAI 2023 Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling ICML 2023 LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning ICLR 2023 Masked Trajectory Models for Prediction, Representation, and Control ICML 2023 Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning ICLR 2023 Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels ICML 2023 Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration NeurIPS 2023 Maximum Entropy Population-Based Training for Zero-Shot Human-AI Coordination AAAI 2023 Maximum State Entropy Exploration using Predecessor and Successor Representations NeurIPS 2023 Memory Gym: Partially Observable Challenges to Memory-Based Agents ICLR 2023 Meta-learning Parameterized Skills ICML 2023 MIMEx: Intrinsic Rewards from Masked Input Modeling NeurIPS 2023 Minimum Description Length Control ICLR 2023 Mode-constrained Model-based Reinforcement Learning via Gaussian Processes AISTATS 2023 Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity JMLR 2023 Model-based Offline Reinforcement Learning with Count-based Conservatism ICML 2023 Model-Based Reinforcement Learning for Cavity Filter Tuning L4DC 2023 Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation AAAI 2023 Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators ICML 2023 Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms NeurIPS 2023 Model-Based Simulation for Optimising Smart Reply ACL 2023 Model-Based Uncertainty in Value Functions AISTATS 2023 Model-Free Active Exploration in Reinforcement Learning NeurIPS 2023