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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

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Showing 1481–1490 of 1918 papers

TitleStatusHype
Benchmarking Batch Deep Reinforcement Learning AlgorithmsCode1
Fair Loss: Margin-Aware Reinforcement Learning for Deep Face Recognition—0
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping—0
Q-learning for POMDP: An application to learning locomotion gaits—0
Composite Q-learning: Multi-scale Q-function Decomposition and Separable Optimization—0
Meta-Q-LearningCode0
Deep Coordination GraphsCode0
CAQL: Continuous Action Q-Learning—0
Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Code1
Visual Exploration and Energy-aware Path Planning via Reinforcement LearningCode0
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