Rollout sampling approximate policy iteration
type: Item
instance of: scholarly article
title: Rollout sampling approximate policy iteration
zbMATH Open document ID: 1464.68308
author: Christos Dimitrakakis
author: Michail G. Lagoudakis
published in: Machine Learning
publication date: 2021-06-28T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62D05
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62L15
zbMATH DE Number: 7364052
zbMATH Keywords: reinforcement learning
zbMATH Keywords: approximate policy iteration
zbMATH Keywords: rollouts
zbMATH Keywords: bandit problems
zbMATH Keywords: classification
zbMATH Keywords: sample complexity
MaRDI profile type: Publication
full work available at URL: s10994-008-5069-3
OpenAlex ID: W3099235411
cites work: Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
cites work: Finite-time analysis of the multiarmed bandit problem
cites work: Q3093383
cites work: Q3623997
cites work: Q3266141
cites work: 10.1162/1532443041827907
DOI: 10.1007/S10994-008-5069-3
description: scientific article; zbMATH DE number 7364052