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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 571–580 of 1918 papers

TitleStatusHype
A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT—0
Cycles and collusion in congestion games under Q-learning—0
Curriculum Q-Learning for Visual Vocabulary Acquisition—0
A Reinforcement Learning Approach to Dairy Farm Battery Management using Q Learning—0
Cross Learning in Deep Q-Networks—0
A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow—0
Criticality-Based Varying Step-Number Algorithm for Reinforcement Learning—0
Credit-cognisant reinforcement learning for multi-agent cooperation—0
A Reinforcement Learning Approach for Process Parameter Optimization in Additive Manufacturing—0
A Flexible Framework for Incorporating Patient Preferences Into Q-Learning—0
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