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Deep RL

3861 directly classified papers

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Papers

Task-Agnostic Dynamics Priors for Deep Reinforcement Learning ICML 2019
Dead-ends and Secure Exploration in Reinforcement Learning ICML 2019
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN ICML 2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms ICML 2019
Off-Policy Deep Reinforcement Learning without Exploration ICML 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning ICML 2019
An Investigation of Model-Free Planning ICML 2019
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning ICML 2019
Composing Entropic Policies using Divergence Correction ICML 2019
Actor-Attention-Critic for Multi-Agent Reinforcement Learning ICML 2019
A Deep Reinforcement Learning Perspective on Internet Congestion Control ICML 2019
Neural Logic Reinforcement Learning ICML 2019
Discovering Options for Exploration by Minimizing Cover Time ICML 2019
Policy Consolidation for Continual Reinforcement Learning ICML 2019
Collaborative Evolutionary Reinforcement Learning ICML 2019
Distilling Policy Distillation AISTATS 2019
Active Exploration in Markov Decision Processes AISTATS 2019
Learning Action Representations for Reinforcement Learning ICML 2019
Structured agents for physical construction ICML 2019
HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving ICML 2019
Distributional reinforcement learning with linear function approximation AISTATS 2019
Credit Assignment Techniques in Stochastic Computation Graphs AISTATS 2019
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup RSS 2019
LeTS-Drive: Driving in a Crowd by Learning from Tree Search RSS 2019
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective AISTATS 2019