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A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning

Geramifard, Alborz, Walsh, Thomas J., Stefanie, Tellex, Chowdhary, Girish

Omschrijving

A Markov Decision Process (MDP) is a natural framework for formulating sequential decision-making problems under uncertainty. In recent years, researchers have greatly advanced algorithms for learning and acting in MDPs. This book reviews such algorithms.

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Schrijver: Geramifard, Alborz, Walsh, Thomas J., Stefanie, Tellex, Chowdhary, Girish
Titel: A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning
Uitgever: now publishers Inc

Jaar: 2013
Taal: Engels
Pagina's: 92
Gewicht: 143 gr

EAN: 9781601987600
Afmetingen: 234 x 156 x 5 mm
Bindwijze: Paperback

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A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning

Geramifard, Alborz, Walsh, Thomas J., Stefanie, Tellex, Chowdhary, Girish

Omschrijving

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