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Reinforcement Learning

7,982 papers (84 classified directly here)

Subtopics

Methods (6,493) Applications (2,922)

Papers per year

9
43
48
875
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Papers (including subtopics)

A Nonparametric Off-Policy Policy Gradient AISTATS 2020
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning AISTATS 2020
Nested-Wasserstein Self-Imitation Learning for Sequence Generation AISTATS 2020
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions AISTATS 2020
Variance Reduction for Evolution Strategies via Structured Control Variates AISTATS 2020
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity AISTATS 2020
Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration AISTATS 2020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020
Conservative Exploration in Reinforcement Learning AISTATS 2020
Value Preserving State-Action Abstractions AISTATS 2020
Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning AISTATS 2020
Frequentist Regret Bounds for Randomized Least-Squares Value Iteration AISTATS 2020
Discrete Action On-Policy Learning with Action-Value Critic AISTATS 2020
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020
Truly Batch Model-Free Inverse Reinforcement Learning about Multiple Intentions AISTATS 2020
Momentum in Reinforcement Learning AISTATS 2020
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning AISTATS 2020
Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity AISTATS 2020
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020
Bayesian Reinforcement Learning via Deep, Sparse Sampling AISTATS 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning AISTATS 2020
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning AISTATS 2020
Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020
Asymptotically Efficient Off-Policy Evaluation for Tabular Reinforcement Learning AISTATS 2020
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020