← Methods
Reinforcement Learning › Methods ›

Policy Learning

2068 directly classified papers

Papers per year

Papers

Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality NIPS 2021
Invariant Causal Imitation Learning for Generalizable Policies NIPS 2021
Exact Asymptotics for Linear Quadratic Adaptive Control JMLR 2021
Partial Policy Iteration for L1-Robust Markov Decision Processes JMLR 2021
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation NAACL 2021
Exploring Dynamic Selection of Branch Expansion Orders for Code Generation ACL 2021
A Regret Minimization Approach to Iterative Learning Control ICML 2021
Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations ICML 2021
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm ICML 2021
Leveraging Non-uniformity in First-order Non-convex Optimization ICML 2021
[RETRACTED] WeaSuL: Weakly Supervised Dialogue Policy Learning: Reward Estimation for Multi-turn Dialogue ACL 2021
Meta-Reinforcement Learning for Mastering Multiple Skills and Generalizing across Environments in Text-based Games ACL 2021
Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning ICML 2021
RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation ACL 2021
UCB Momentum Q-learning: Correcting the bias without forgetting ICML 2021
PC-MLP: Model-based Reinforcement Learning with Policy Cover Guided Exploration ICML 2021
Near Optimal Reward-Free Reinforcement Learning ICML 2021
Latent Skill Planning for Exploration and Transfer ICLR 2021
When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence AISTATS 2021
Hierarchical Neural Dynamic Policies RSS 2021
Reward-Constrained Behavior Cloning IJCAI 2021
Hindsight Trust Region Policy Optimization IJCAI 2021
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks IJCAI 2021
Deep Reinforcement Learning with Hierarchical Structures IJCAI 2021
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity NIPS 2021