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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 1471–1480 of 1918 papers

TitleStatusHype
Control-Tutored Reinforcement Learning: an application to the Herding Problem—0
Join Query Optimization with Deep Reinforcement Learning AlgorithmsCode0
Adaptive Modulation and Coding based on Reinforcement Learning for 5G Networks—0
A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control—0
Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning—0
Which Channel to Ask My Question? Personalized Customer Service RequestStream Routing using DeepReinforcement Learning—0
Efficient Drone Mobility Support Using Reinforcement Learning—0
Quantum Observables for continuous control of the Quantum Approximate Optimization Algorithm via Reinforcement Learning—0
Asymptotics of Reinforcement Learning with Neural Networks—0
Modelling Bahdanau Attention using Election methods aided by Q-Learning—0
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