TAILIEUCHUNG - ADVANCES IN REINFORCEMENT LEARNING

The MATLAB BVP solver of bvp4c is introduced as a Residual control based, adaptive mesh solver. An adaptive mesh solver is an alternative approach to that of a uniform mesh, which would specify a uniform grid of data points xi over the interval [xi, xi+1] and solve accordingly. The adaptive solver will adjust the mesh points at each stage in the iterative procedure, distributing them to points where they are most needed. This can lead to obvious advantages in terms of computational and storage costs as well as allowing control over the grid resolution. The concept of a residual is the cornerstone of the bvp4c framework;. | ADVANCES IN REINFORCEMENT LEARNING Edited by Abdelhamid Mellouk Advances in Reinforcement Learning Edited by Abdelhamid Mellouk Published by InTech Janeza Trdine 9 51000 Rijeka Croatia Copyright 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution license which permits to copy distribute transmit and adapt the work in any medium so long as the original work is properly cited. After this work has been published by InTech authors have the right to republish it in whole or part in any publication of which they are the author and to make other personal use of the work. Any republication referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials instructions methods or ideas contained in the book. Publishing Process Manager Jelena Marusic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright ilolab 2010. Used under license from First published January 2011 Printed in India A free online edition of this book is available at Additional hard copies can be obtained from orders@ Advances in Reinforcement Learning Edited by Abdelhamid Mellouk p. cm. ISBN 978-953-307-369-9 I kfTC LI OPEN ACCESS INI Evn PUBLISHER INTECH open free online editions of InTech Books and Journals can be found at .

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