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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 1071–1080 of 1918 papers

TitleStatusHype
QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning—0
Quadratic Q-network for Learning Continuous Control for Autonomous Vehicles—0
Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping—0
Quantitative Trading using Deep Q Learning—0
Quantum Architecture Search via Continual Reinforcement Learning—0
Quantum deep Q learning with distributed prioritized experience replay—0
Quantum deep recurrent reinforcement learning—0
Quantum-Inspired Reinforcement Learning in the Presence of Epistemic Ambivalence—0
Quantum Observables for continuous control of the Quantum Approximate Optimization Algorithm via Reinforcement Learning—0
Deep Reinforcement Learning via L-BFGS Optimization—0
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