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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 1841–1850 of 1918 papers

TitleStatusHype
Equivalence Between Policy Gradients and Soft Q-Learning—0
Reinforcement Learning with External Knowledge and Two-Stage Q-functions for Predicting Popular Reddit Threads—0
Deep Q-learning from DemonstrationsCode0
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation—0
Pseudorehearsal in value function approximation—0
Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing—0
Multi-step Reinforcement Learning: A Unifying Algorithm—0
Bridging the Gap Between Value and Policy Based Reinforcement Learning—0
Reinforcement Learning with Deep Energy-Based PoliciesCode0
Learning Control for Air Hockey Striking using Deep Reinforcement Learning—0
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