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Q-Learning

The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

( Image credit: Playing Atari with Deep Reinforcement Learning )

Papers

Showing 17511775 of 1918 papers

TitleStatusHype
Q-CP: Learning Action Values for Cooperative Planning0
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy MethodsCode0
Variance Reduction Methods for Sublinear Reinforcement Learning0
Addressing Function Approximation Error in Actor-Critic MethodsCode1
Temporal Difference Models: Model-Free Deep RL for Model-Based Control0
Weighted Double Deep Multiagent Reinforcement Learning in Stochastic Cooperative Environments0
Efficient Collaborative Multi-Agent Deep Reinforcement Learning for Large-Scale Fleet ManagementCode0
A Deep Q-Learning Agent for the L-Game with Variable Batch TrainingCode0
Monte Carlo Q-learning for General Game PlayingCode0
Prioritized Sweeping Neural DynaQ with Multiple Predecessors, and Hippocampal Replays0
Mean Field Multi-Agent Reinforcement LearningCode1
Q-learning with Nearest Neighbors0
M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search0
Balancing Two-Player Stochastic Games with Soft Q-Learning0
Deep Reinforcement Learning using Capsules in Advanced Game Environments0
Using deep Q-learning to understand the tax evasion behavior of risk-averse firmsCode0
The QLBS Q-Learner Goes NuQLear: Fitted Q Iteration, Inverse RL, and Option Portfolios0
Deep Reinforcement Fuzzing0
DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic NavigationCode0
Trading the Twitter Sentiment with Reinforcement Learning0
Faster Deep Q-learning using Neural Episodic Control0
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic ActorCode1
ViZDoom: DRQN with Prioritized Experience Replay, Double-Q Learning, & Snapshot Ensembling0
ScreenerNet: Learning Self-Paced Curriculum for Deep Neural Networks0
Autonomous Vehicle Fleet Coordination With Deep Reinforcement Learning0
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