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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 1851–1860 of 1918 papers

TitleStatusHype
Designing Neural Network Architectures using Reinforcement LearningCode0
Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality TighteningCode0
A Differentiable Physics Engine for Deep Learning in Robotics—0
Combining policy gradient and Q-learning—0
Using a Deep Reinforcement Learning Agent for Traffic Signal Control—0
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear—0
Internet of Things Applications: Animal Monitoring with Unmanned Aerial Vehicle—0
Active exploration in parameterized reinforcement learningCode0
Modelling Stock-market Investors as Reinforcement Learning Agents [Correction]—0
Playing FPS Games with Deep Reinforcement LearningCode0
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