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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 1371–1380 of 1918 papers

TitleStatusHype
Online Antenna Tuning in Heterogeneous Cellular Networks with Deep Reinforcement Learning—0
On-line Building Energy Optimization using Deep Reinforcement Learning—0
Online Frequency Scheduling by Learning Parallel Actions—0
Online inductive learning from answer sets for efficient reinforcement learning exploration—0
Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing—0
Online Robust Reinforcement Learning with Model Uncertainty—0
Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data—0
Asymptotic Analysis of Sample-averaged Q-learning—0
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs—0
Online Transfer Learning in Reinforcement Learning Domains—0
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