conftrace_
← Methods
Reinforcement Learning › Methods ›

Policy Learning

2,076 papers

Papers per year

23
23
216
153
'10
'15
'20
'25

Papers

Efficient Policy Learning from Surrogate-Loss Classification Reductions ICML 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences ICML 2020
Provably Efficient Exploration in Policy Optimization ICML 2020
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills ICML 2020
Optimizing for the Future in Non-Stationary MDPs ICML 2020
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism ICML 2020
Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models ICML 2020
Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning ICML 2020
Monte-Carlo Tree Search as Regularized Policy Optimization ICML 2020
Momentum-Based Policy Gradient Methods ICML 2020
From Importance Sampling to Doubly Robust Policy Gradient ICML 2020
Generalization to New Actions in Reinforcement Learning ICML 2020
Statistically Efficient Off-Policy Policy Gradients ICML 2020
What can I do here? A Theory of Affordances in Reinforcement Learning ICML 2020
Domain Adaptive Imitation Learning ICML 2020
Asynchronous Coagent Networks ICML 2020
Controlling Overestimation Bias with Truncated Mixture of Continuous Distributional Quantile Critics ICML 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020
Learning to Score Behaviors for Guided Policy Optimization ICML 2020
Structured Policy Iteration for Linear Quadratic Regulator ICML 2020
Reducing Sampling Error in Batch Temporal Difference Learning ICML 2020
Learning Selection Strategies in Buchberger’s Algorithm ICML 2020
Learning Human Objectives by Evaluating Hypothetical Behavior ICML 2020
Constrained Markov Decision Processes via Backward Value Functions ICML 2020
Off-Policy Actor-Critic with Shared Experience Replay ICML 2020