Policy Learning

Stabilizing Policy Gradients for Stochastic Differential Equations via Consistency with Perturbation Process ICML 2024 State-free Reinforcement Learning NeurIPS 2024 Stop! Planner Time: Metareasoning for Probabilistic Planning Using Learned Performance Profiles AAAI 2024 Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets ICLR 2024 Submodular Reinforcement Learning ICLR 2024 Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning NeurIPS 2024 Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning NeurIPS 2024 SUF: Stabilized Unconstrained Fine-Tuning for Offline-to-Online Reinforcement Learning AAAI 2024 Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks CoRL 2024 Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization ICML 2024 Synthesizing Programmatic Policy for Generalization within Task Domain IJCAI 2024 TA&AT: Enhancing Task-Oriented Dialog with Turn-Level Auxiliary Tasks and Action-Tree Based Scheduled Sampling AAAI 2024 Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation ICML 2024 Taking Action Towards Graceful Interaction: The Effects of Performing Actions on Modelling Policies for Instruction Clarification Requests EACL 2024 TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient AAAI 2024 Teaching Embodied Reinforcement Learning Agents: Informativeness and Diversity of Language Use EMNLP 2024 The Accuracy Paradox in RLHF: When Better Reward Models Don’t Yield Better Language Models EMNLP 2024 The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm ICML 2024 The Non-linear F-Design and Applications to Interactive Learning ICML 2024 The surprising efficiency of temporal difference learning for rare event prediction NeurIPS 2024 Time-Efficient Reinforcement Learning with Stochastic Stateful Policies ICLR 2024 Timing as an Action: Learning When to Observe and Act AISTATS 2024 ToolPlanner: A Tool Augmented LLM for Multi Granularity Instructions with Path Planning and Feedback EMNLP 2024 To the Max: Reinventing Reward in Reinforcement Learning ICML 2024 Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL AISTATS 2024