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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 1021–1030 of 1918 papers

TitleStatusHype
Fair Loss: Margin-Aware Reinforcement Learning for Deep Face Recognition—0
Fast Adaptive Anti-Jamming Channel Access via Deep Q Learning and Coarse-Grained Spectrum Prediction—0
Fast Block Linear System Solver Using Q-Learning Schduling for Unified Dynamic Power System Simulations—0
Fast constraint satisfaction problem and learning-based algorithm for solving Minesweeper—0
GLSearch: Maximum Common Subgraph Detection via Learning to Search—0
Faster Deep Q-learning using Neural Episodic Control—0
Faster Non-asymptotic Convergence for Double Q-learning—0
Faster Q-Learning Algorithms for Restless Bandits—0
Fastest Convergence for Q-learning—0
Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network—0
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