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Deep RL

3861 directly classified papers

Papers per year

Papers

RL-GAN-Net: A Reinforcement Learning Agent Controlled GAN Network for Real-Time Point Cloud Shape Completion CVPR 2019
Generalization of Reinforcement Learners with Working and Episodic Memory NIPS 2019
Explicit Explore-Exploit Algorithms in Continuous State Spaces NIPS 2019
Language as an Abstraction for Hierarchical Deep Reinforcement Learning NIPS 2019
Generalized Off-Policy Actor-Critic NIPS 2019
Discovery of Useful Questions as Auxiliary Tasks NIPS 2019
Learning Local Search Heuristics for Boolean Satisfiability NIPS 2019
Learning to Perform Local Rewriting for Combinatorial Optimization NIPS 2019
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment NIPS 2019
Learning dynamic polynomial proofs NIPS 2019
RUDDER: Return Decomposition for Delayed Rewards NIPS 2019
Hindsight Credit Assignment NIPS 2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning NIPS 2019
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy NIPS 2019
Interval timing in deep reinforcement learning agents NIPS 2019
Shaping Belief States with Generative Environment Models for RL NIPS 2019
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables NIPS 2019
A Geometric Perspective on Optimal Representations for Reinforcement Learning NIPS 2019
Information-Theoretic Confidence Bounds for Reinforcement Learning NIPS 2019
Worst-Case Regret Bounds for Exploration via Randomized Value Functions NIPS 2019
Explicit Planning for Efficient Exploration in Reinforcement Learning NIPS 2019
A Kernel Loss for Solving the Bellman Equation NIPS 2019
Imitation-Projected Programmatic Reinforcement Learning NIPS 2019
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning NIPS 2019
When to Trust Your Model: Model-Based Policy Optimization NIPS 2019