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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 1441–1450 of 1918 papers

TitleStatusHype
Privacy-Preserving Q-Learning with Functional Noise in Continuous SpacesCode0
Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach—0
Quadratic Q-network for Learning Continuous Control for Autonomous Vehicles—0
QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc NetworksCode0
Join Query Optimization with Deep Reinforcement Learning AlgorithmsCode0
Control-Tutored Reinforcement Learning: an application to the Herding Problem—0
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
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