Adaptive Representations for Reinforcement Learning

Name: Adaptive Representations for Reinforcement Learning
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642139314
Price: 2286 CZK
Availability: InStock

Autor: Shimon Whiteson

Jazyk:

Vazba: Pevná

Vydavatel: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Dostupnost: Skladem u dodavatele

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2 286 Kč

This book presents the main results new algorithms for reinforcement learning, a form of machine lea...

Informace o knize

Autor

Shimon Whiteson

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2010

Stránek

116

EAN

9783642139314

ISBN

3642139310

Enbook ID

01656109

Vydavatel

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Hmotnost

396

Rozměry

155 x 235 x 13

Kompletní popis

This book presents the main results new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks an effective control policy for tackling a sequential decision task. Unlike in supervised learning, the agent never sees examples of correct or incorrect behavior but receives only a reward signal as feedback. This book also introduces a novel method for devising input representations. In particular, it presents a way to find a minimal set of features sufficient to describe the agent s current state, a challenge known as the feature selection problem. In addition to introducing these new methods, this book presents extensive empirical results in multiple domains demonstrating that these techniques can substantially§improve performance over methods with manual representations.

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Adaptive Representations for Reinforcement Learning

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