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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 951–960 of 1918 papers

TitleStatusHype
Transferred Q-learning—0
Intelligent Autonomous Intersection Management—0
Multiple Correlated Jammers Nullification using LSTM-based Deep Dueling Neural Network—0
Stochastic Gradient Descent with Dependent Data for Offline Reinforcement Learning—0
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise—0
Deep Reinforcement Learning with Spiking Q-learning—0
Optimal variance-reduced stochastic approximation in Banach spaces—0
Deep Q-learning: a robust control approachCode0
A Family of Cognitively Realistic Parsing Environments for Deep Reinforcement Learning—0
Criticality-Based Varying Step-Number Algorithm for Reinforcement Learning—0
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