Reinforcement Learning

Evaluating Real-World Robot Manipulation Policies in Simulation CoRL 2024 Evaluating Transformer-Enhanced Deep Reinforcement Learning for Speech Emotion Recognition Interspeech 2024 Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation ACL 2024 Evidential Active Recognition: Intelligent and Prudent Open-World Embodied Perception CVPR 2024 EvIL: Evolution Strategies for Generalisable Imitation Learning ICML 2024 Evolution and learning in differentiable robots RSS 2024 Evolutionary Reward Design and Optimization with Multimodal Large Language Models ACL 2024 EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search ICML 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 Exclusively Penalized Q-learning for Offline Reinforcement Learning NeurIPS 2024 Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch NeurIPS 2024 Expected flow networks in stochastic environments and two-player zero-sum games ICLR 2024 Expediting Reinforcement Learning by Incorporating Knowledge About Temporal Causality in the Environment CLeaR 2024 Experience as Source for Anticipation and Planning: Experiential Policy Learning for Target-driven Recommendation Dialogues EMNLP 2024 Expert Proximity as Surrogate Rewards for Single Demonstration Imitation Learning ICML 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 Careful Design of SVM Solution for Aspect-term Sentiment Analysis EMNLP 2024 Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration NeurIPS 2024 Exploration and Anti-Exploration with Distributional Random Network Distillation ICML 2024 Exploration by Learning Diverse Skills through Successor State Representations NeurIPS 2024 Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring ICML 2024 Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization ICML 2024 Exploration via linearly perturbed loss minimisation AISTATS 2024