Adaptive Representations for Reinforcement Learning

Name: Adaptive Representations for Reinforcement Learning
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642139314
Price: 551.94 RON
Availability: InStock

Autor: Shimon Whiteson

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Legare: Copertă tare

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

Disponibilitate: În depozitul extern

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551.94 lei

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

Informații despre carte

Autor

Shimon Whiteson

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2010

Pagini

116

EAN

9783642139314

ISBN

3642139310

Enbook ID

01656109

Editura

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Greutate

396

Dimensiuni

155 x 235 x 13

Descriere completă

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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Descriere completă

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