Reinforcement Learning

Effect-Invariant Mechanisms for Policy Generalization JMLR 2024 Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning NeurIPS 2024 Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems AISTATS 2024 Efficient Variational Sequential Information Control AISTATS 2024 Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence EMNLP 2024 Enhancing Chess Reinforcement Learning with Graph Representation NeurIPS 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation NeurIPS 2024 Enhancing Off-Policy Constrained Reinforcement Learning through Adaptive Ensemble C Estimation AAAI 2024 Enhancing Reinforcement Learning with Dense Rewards from Language Model Critic EMNLP 2024 Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach NeurIPS 2024 Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning NeurIPS 2024 Enhancing Temporal Sensitivity and Reasoning for Time-Sensitive Question Answering EMNLP 2024 EnMatch: Matchmaking for Better Player Engagement via Neural Combinatorial Optimization AAAI 2024 Episodic Return Decomposition by Difference of Implicitly Assigned Sub-trajectory Reward AAAI 2024 ERL-TD: Evolutionary Reinforcement Learning Enhanced with Truncated Variance and Distillation Mutation AAAI 2024 Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation NAACL 2024 Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation NeurIPS 2024 Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption AAAI 2024 Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking NeurIPS 2024 Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch NeurIPS 2024 Explaining Reinforcement Learning Agents through Counterfactual Action Outcomes AAAI 2024 Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning (Abstract Reprint) AAAI 2024 Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration NeurIPS 2024 Exploration by Learning Diverse Skills through Successor State Representations NeurIPS 2024 Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning NeurIPS 2024