deep reinforcement learning

903 papers

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Also known as

DRQN DEEP RL DDQ DQN DRL DRL NULL DRL OR NULL DQFD RL

Co-occurring keywords

reinforcement learning (4122) policy learning (699) sample efficiency (469) neural network (6616) continuous control (246) multi-agent system (1743) policy gradient (518) policy optimization (630) value function (294) off-policy learning (227)

Papers

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems ICML 2020

MRI Reconstruction with Interpretable Pixel-Wise Operations Using Reinforcement Learning AAAI 2020

Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning AAAI 2020

Exploratory Combinatorial Optimization with Reinforcement Learning AAAI 2020

Deterministic Value-Policy Gradients AAAI 2020

On the Role of Weight Sharing During Deep Option Learning AAAI 2020

Deep Reinforcement Learning for Active Human Pose Estimation AAAI 2020

ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract) AAAI 2020

Learning When and Where to Zoom With Deep Reinforcement Learning CVPR 2020

A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning ACML 2020

Learning to Walk in the Real World with Minimal Human Effort CORL 2020

Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learning CORL 2020

Policy learning in SE(3) action spaces CORL 2020

Deep Reactive Planning in Dynamic Environments CORL 2020

Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control CORL 2020

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments CORL 2020

Stable Policy Optimization via Off-Policy Divergence Regularization UAI 2020

Efficient Object Detection in Large Images Using Deep Reinforcement Learning WACV 2020

ExpanRL: Hierarchical Reinforcement Learning for Course Concept Expansion in MOOCs AACL 2020

A Theoretical Analysis of Deep Q-Learning L4DC 2020

Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients ICML 2020

Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling ICML 2020

Responsive Safety in Reinforcement Learning by PID Lagrangian Methods ICML 2020

Reinforcement Learning for Integer Programming: Learning to Cut ICML 2020

A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation ICML 2020