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Policy Learning

2068 directly classified papers

Papers per year

Papers

Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation NIPS 2024
Recurrent Reinforcement Learning with Memoroids NIPS 2024
Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification NIPS 2024
POLICEd RL: Learning Closed-Loop Robot Control Policies with Provable Satisfaction of Hard Constraints RSS 2024
Aligner²: Enhancing Joint Multiple Intent Detection and Slot Filling via Adjustive and Forced Cross-Task Alignment AAAI 2024
Policy-shaped prediction: avoiding distractions in model-based reinforcement learning NIPS 2024
P2BPO: Permeable Penalty Barrier-Based Policy Optimization for Safe RL AAAI 2024
Robust Reinforcement Learning with General Utility NIPS 2024
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games AISTATS 2024
Solving Non-rectangular Reward-Robust MDPs via Frequency Regularization AAAI 2024
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes AISTATS 2024
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games NIPS 2024
Omega-Regular Decision Processes AAAI 2024
A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning AISTATS 2024
Provable Policy Gradient Methods for Average-Reward Markov Potential Games AISTATS 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes NIPS 2024
Anytime-Constrained Reinforcement Learning AISTATS 2024
Generative Flow Networks as Entropy-Regularized RL AISTATS 2024
Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator NIPS 2024
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems AISTATS 2024
Independent Learning in Constrained Markov Potential Games AISTATS 2024
Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms NIPS 2024
Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning AAAI 2024
Timing as an Action: Learning When to Observe and Act AISTATS 2024
Resilient Constrained Reinforcement Learning AISTATS 2024