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Deep RL

4,525 papers

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Papers

Agnostic Q-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity NeurIPS 2020 A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning AISTATS 2020 AI-Toolbox: A C++ library for Reinforcement Learning and Planning (with Python Bindings) JMLR 2020 A Learning Based Branch and Bound for Maximum Common Subgraph Related Problems AAAI 2020 A Learning-based Iterative Method for Solving Vehicle Routing Problems ICLR 2020 A Learning-Exploring Method to Generate Diverse Paraphrases with Multi-Objective Deep Reinforcement Learning COLING 2020 Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction AAAI 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 A Local Temporal Difference Code for Distributional Reinforcement Learning NeurIPS 2020 A Machine of Few Words: Interactive Speaker Recognition with Reinforcement Learning Interspeech 2020 A Markov Decision Process Model for Socio-Economic Systems Impacted by Climate Change ICML 2020 Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent IJCAI 2020 An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search NeurIPS 2020 An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization IJCAI 2020 An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay NeurIPS 2020 An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies AAAI 2020 An Optimistic Perspective on Offline Reinforcement Learning ICML 2020 A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances NeurIPS 2020 Answer-driven Deep Question Generation based on Reinforcement Learning COLING 2020 A Reduction from Reinforcement Learning to No-Regret Online Learning AISTATS 2020 A Self-Tuning Actor-Critic Algorithm NeurIPS 2020 A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning ACML 2020 A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound AAAI 2020 Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset AAAI 2020 A Theoretical Analysis of Deep Q-Learning L4DC 2020