Latest papers can be found here.
The Predictron: End-To-End Learning and Planning
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
Trust Region Policy Optimization (TRPO)
Reinforcement Learning with Unsupervised Auxiliary Tasks (UNREAL)
Learning to reinforcement learn
Deep Reinforcement Learning for Visual Object Tracking in Videos
Learning to Act by Predicting the Future
Neural Map: Structured Memory for Deep Reinforcement Learning
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Hybrid computing using a neural network with dynamic external memory
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation
Learning from Demonstrations for Real World Reinforcement Learning
DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning
Automatic Goal Generation for Reinforcement Learning Agents
Hindsight Experience Replay
Emergence of Locomotion Behaviours in Rich Environments
Proximal Policy Optimization Algorithms
Reverse Curriculum Generation for Reinforcement Learning
The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously
Learning model-based planning from scratch
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
The Uncertainty Bellman Equation and Exploration
Distral: Robust Multitask Reinforcement Learning
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
Emergent Complexity via Multi-agent Competition
Rainbow: Combining Improvements in Deep Reinforcement Learning
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
Imagination-Augmented Agents for Deep Reinforcement Learning
Divide-and-Conquer Reinforcement Learning
Action Branching Architectures for Deep Reinforcement Learning
Time Limits in Reinfocement Learning
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Mastering the game of Go without human knowledge
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Learning an Embedding Space for Transferable Robot Skills
Zero-Shot Visual Imitation
Motion Planning Networks
Counterfactual Multi-Agent Policy Gradients
Learning to Adapt: Meta-Learning for Model-Based Control
Hierarchical Imitation and Reinforcement Learning
SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning
Model-Based Reinforcement Learning via Meta-Policy Optimization