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Robocup Soccer Training

Jose Antonio Alija

ISBN 10: 3838355970 / ISBN 13: 9783838355979
Editorial: LAP Lambert Academic Publishing
Nuevos Condición: New Encuadernación de tapa blanda
Librería: BuySomeBooks (Las Vegas, NV, Estados Unidos de America)

Librería en AbeBooks desde: 21 de mayo de 2012

Cantidad: > 20

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Descripción

Paperback. 112 pages. Dimensions: 8.7in. x 5.9in. x 0.3in.RoboCup soccer, an education initiative and a solid platform for Machine Learning and robotics international research. RoboCup, provides a high dimensional state and action space multi-agent problem, in which autonomous agents have to work collectively to achieve a common goal; (in this case) with their teammates (other robots) to win the match. Few has been written about RoboCup Soccer that provides a full framework about practical implementation of Reinforcement learning algorithms in this field, being this the first purpose of this book, take the reader to applied artificial intelligence. Also this book compares two Reinforcement Learning algorithms applied to learning RoboCup skills, two individual skills (Move to position, Intercept) and a multi-agent skill: Keepaway, proposed by Peter Stone in 2D, then scaling this skill to the 3D server, providing the results of which algorithm is better for each kind of problem. The research and results presented in this book cover remarkable topics for researchers, students and anyone interested in Reinforcement Learning or anyone else involved or participating in RoboCup soccer world cup. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. N° de ref. de la librería 9783838355979

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Detalles bibliográficos

Título: Robocup Soccer Training

Editorial: LAP Lambert Academic Publishing

Encuadernación: Paperback

Condición del libro:New

Tipo de libro: Paperback

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Sinopsis:

RoboCup soccer, an education initiative and a solid platform for Machine Learning and robotics international research. RoboCup, provides a high dimensional state and action space multi-agent problem, in which autonomous agents have to work collectively to achieve a common goal; (in this case) with their teammates (other robots) to win the match. Few has been written about RoboCup Soccer that provides a full framework about practical implementation of Reinforcement learning algorithms in this field, being this the first purpose of this book, take the reader to applied artificial intelligence. Also this book compares two Reinforcement Learning algorithms applied to learning RoboCup skills, two individual skills (Move to position, Intercept) and a multi-agent skill: Keepaway, proposed by Peter Stone in 2D, then scaling this skill to the 3D server, providing the results of which algorithm is better for each kind of problem. The research and results presented in this book cover remarkable topics for researchers, students and anyone interested in Reinforcement Learning or anyone else involved or participating in RoboCup soccer world cup.

About the Author:

Graduated with a B.Sc. degree in Computer Systems at Mexico City, afterwards he received his M.Sc. degree with distinction in Advanced Computing (Machine Learning & Data Mining) at Bristol University, UK. Currently he is Business Intelligence and Data Mining Coordinator at Pfizer, México

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