← Methods
Reinforcement Learning › Methods ›

Policy Learning

2068 directly classified papers

Papers per year

Papers

Low-rank MDPs with Continuous Action Spaces AISTATS 2024
Meta-learning linear quadratic regulators: a policy gradient MAML approach for model-free LQR L4DC 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs NIPS 2024
Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality JMLR 2024
NeoRL: Efficient Exploration for Nonepisodic RL NIPS 2024
On the uniqueness of solution for the Bellman equation of LTL objectives L4DC 2024
Data-Efficient Policy Evaluation Through Behavior Policy Search JMLR 2024
Learning Optimal Advantage from Preferences and Mistaking It for Reward AAAI 2024
F2RL: Factuality and Faithfulness Reinforcement Learning Framework for Claim-Guided Evidence-Supported Counterspeech Generation EMNLP 2024
ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback EMNLP 2024
A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning NIPS 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property AAAI 2024
Hierarchical Planning and Learning for Robots in Stochastic Settings Using Zero-Shot Option Invention AAAI 2024
Dynamic Multi-Reward Weighting for Multi-Style Controllable Generation EMNLP 2024
Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning NIPS 2024
Risk-sensitive control as inference with Rényi divergence NIPS 2024
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment NIPS 2024
GO-DICE: Goal-Conditioned Option-Aware Offline Imitation Learning via Stationary Distribution Correction Estimation AAAI 2024
A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective NIPS 2024
Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables AAAI 2024
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization AAAI 2024
Mitigating Open-Vocabulary Caption Hallucinations EMNLP 2024
C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory NIPS 2024
Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms AAAI 2024
Dynamic Reward Adjustment in Multi-Reward Reinforcement Learning for Counselor Reflection Generation COLING 2024