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Policy Learning

2068 directly classified papers

Papers per year

Papers

Towards High-Level Intrinsic Exploration in Reinforcement Learning IJCAI 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
Domain Adaptive Imitation Learning ICML 2020
Asynchronous Coagent Networks 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
Optimistic Policy Optimization with Bandit Feedback ICML 2020
Predictive Coding for Locally-Linear Control ICML 2020
Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards ICML 2020
Policy Improvement via Imitation of Multiple Oracles NIPS 2020
Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies ICML 2020
Strictly Batch Imitation Learning by Energy-based Distribution Matching NIPS 2020
Taylor Expansion Policy Optimization ICML 2020
Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions ICML 2020
Concept2Robot: Learning Manipulation Concepts from Instructions and Human Demonstrations RSS 2020
Learning solutions to hybrid control problems using Benders cuts L4DC 2020