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Deep RL

3,886 papers

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Papers

Distral: Robust multitask reinforcement learning NIPS 2017
Hybrid Reward Architecture for Reinforcement Learning NIPS 2017
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning NIPS 2017
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning NIPS 2017
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes NIPS 2017
Multi-View Decision Processes: The Helper-AI Problem NIPS 2017
Decoding with Value Networks for Neural Machine Translation NIPS 2017
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS 2017
Shallow Updates for Deep Reinforcement Learning NIPS 2017
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning NIPS 2017
Hindsight Experience Replay NIPS 2017
Learning Unknown Markov Decision Processes: A Thompson Sampling Approach NIPS 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks NIPS 2017
Safe Model-based Reinforcement Learning with Stability Guarantees NIPS 2017
Reinforcement Learning under Model Mismatch NIPS 2017
Teaching Machines to Describe Images with Natural Language Feedback NIPS 2017
Imagination-Augmented Agents for Deep Reinforcement Learning NIPS 2017
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning NIPS 2017
Runtime Neural Pruning NIPS 2017
Boltzmann Exploration Done Right NIPS 2017
Dynamic-Depth Context Tree Weighting NIPS 2017
Deep Reinforcement Learning from Human Preferences NIPS 2017
Learning Combinatorial Optimization Algorithms over Graphs NIPS 2017
Natural Value Approximators: Learning when to Trust Past Estimates NIPS 2017
Value Prediction Network NIPS 2017