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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 126150 of 1918 papers

TitleStatusHype
A Stochastic Game Framework for Efficient Energy Management in Microgrid NetworksCode1
Discriminator Soft Actor Critic without Extrinsic RewardsCode1
An Optimistic Perspective on Offline Deep Reinforcement LearningCode1
Benchmarking Batch Deep Reinforcement Learning AlgorithmsCode1
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Code1
ModelicaGym: Applying Reinforcement Learning to Modelica ModelsCode1
An Optimistic Perspective on Offline Reinforcement LearningCode1
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and NeuropsychiatryCode1
Split Q Learning: Reinforcement Learning with Two-Stream RewardsCode1
Boosting Soft Actor-Critic: Emphasizing Recent Experience without Forgetting the PastCode1
SQIL: Imitation Learning via Reinforcement Learning with Sparse RewardsCode1
Optimization of Molecules via Deep Reinforcement LearningCode1
Negative Update Intervals in Deep Multi-Agent Reinforcement LearningCode1
Is Q-learning Provably Efficient?Code1
Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement LearningCode1
Addressing Function Approximation Error in Actor-Critic MethodsCode1
Mean Field Multi-Agent Reinforcement LearningCode1
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic ActorCode1
Automated Cloud Provisioning on AWS using Deep Reinforcement LearningCode1
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive EnvironmentsCode1
Evolution Strategies as a Scalable Alternative to Reinforcement LearningCode1
Stabilising Experience Replay for Deep Multi-Agent Reinforcement LearningCode1
Continuous Deep Q-Learning with Model-based AccelerationCode1
Multiagent Cooperation and Competition with Deep Reinforcement LearningCode1
Deep Reinforcement Learning with Double Q-learningCode1
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