Learning Continuous Control Policies by Stochastic Value Gradients

Towards Vision-Based Deep Reinforcement Learning for Robotic Motion
Control

Deep Reinforcement Learning in Parameterized Action Space

Prioritized Experience Replay

Dueling Network Architectures for Deep Reinforcement Learning

How to Discount Deep Reinforcement Learning: Towards New Dynamic
Strategies

Deep Attention Recurrent Q-Network

Policy Distillation

Increasing the Action Gap: New Operators for Reinforcement Learning

State of the Art Control of Atari Games Using Shallow Reinforcement
Learning

On Learning to Think: Algorithmic Information Theory for Novel
Combinations of Reinforcement Learning Controllers and Recurrent Neural
World Models

Memory-based control with recurrent neural networks

Mastering the game of Go with deep neural networks and tree search

Asynchronous Methods for Deep Reinforcement Learning

Graying the black box: Understanding DQNs

Learning to Communicate to Solve Riddles with Deep Distributed Recurrent
Q-Networks

Deep Exploration via Bootstrapped DQN

Using Deep Q-Learning to Control Optimization Hyperparameters

Value Iteration Networks

Weight Normalization : A Simple Reparameterization to Accelerate
Training of Deep Neural Networks

Continuous Deep Q-Learning with Model-based Acceleration

Deep Reinforcement Learning from Self-Play in Imperfect-Information
Games

Learning Visual Predictive Models of Physics for Playing Billiards

Hierarchical Deep Reinforcement Learning: Integrating Temporal
Abstraction and Intrinsic Motivation

Control of Memory, Active Perception, and Action in Minecraft

Deep Successor Reinforcement Learning

Learning Deep Control Policies for Autonomous Aerial Vehicles with
MPC-Guided Policy Search

Model-Free Episodic Control