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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 1231–1240 of 1918 papers

TitleStatusHype
Long and Short Memory Balancing in Visual Co-Tracking using Q-Learning—0
Long-term Fairness in Ride-Hailing Platform—0
Long-term planning, short-term adjustments—0
LOQA: Learning with Opponent Q-Learning Awareness—0
MA2QL: A Minimalist Approach to Fully Decentralized Multi-Agent Reinforcement Learning—0
Machine learning-based decentralized TDMA for VLC IoT networks—0
Machine Learning Empowered Trajectory and Passive Beamforming Design in UAV-RIS Wireless Networks—0
MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework—0
Managing App Install Ad Campaigns in RTB: A Q-Learning Approach—0
Manipulating Reinforcement Learning: Poisoning Attacks on Cost Signals—0
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