← Methods
Reinforcement Learning › Methods ›

Policy Learning

2068 directly classified papers

Papers per year

Papers

Marginal Utility for Planning in Continuous or Large Discrete Action Spaces NIPS 2020
Online learning with dynamics: A minimax perspective NIPS 2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems JMLR 2020
Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss NIPS 2020
Information Theoretic Regret Bounds for Online Nonlinear Control NIPS 2020
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems NIPS 2020
Can We Learn Heuristics for Graphical Model Inference Using Reinforcement Learning? CVPR 2020
Lifelong Learning with a Changing Action Set AAAI 2020
Combining Cognitive Modeling and Reinforcement Learning for Clarification in Dialogue COLING 2020
Elaborating on Learned Demonstrations with Temporal Logic Specifications RSS 2020
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal COLT 2020
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020
Stable Policy Optimization via Off-Policy Divergence Regularization UAI 2020
Policy learning in SE(3) action spaces CORL 2020
Semi-Supervised Dialogue Policy Learning via Stochastic Reward Estimation ACL 2020
Conversational Graph Grounded Policy Learning for Open-Domain Conversation Generation ACL 2020
Pessimism About Unknown Unknowns Inspires Conservatism COLT 2020
Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learning CORL 2020
Learning Efficient Dialogue Policy from Demonstrations through Shaping ACL 2020
Stylized Text Generation: Approaches and Applications ACL 2020
Interactive Imitation Learning in State-Space CORL 2020
Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation L4DC 2020
A Duality Approach for Regret Minimization in Average-Award Ergodic Markov Decision Processes L4DC 2020
Optimistic robust linear quadratic dual control L4DC 2020
Partially Observable Markov Decision Process Modelling for Assessing Hierarchies ACML 2020