Advanced Methodologies for Bayesian Networks Second International Wo
This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were
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Joe Suzuki Maomi Ueno (Eds.)
Advanced Methodologies for Bayesian Networks Second International Workshop, AMBN 2015 Yokohama, Japan, November 16–18, 2015 Proceedings
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Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
LNAI Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
LNAI Founding Series Editor Joerg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/1244
Joe Suzuki Maomi Ueno (Eds.) •
Advanced Methodologies for Bayesian Networks Second International Workshop, AMBN 2015 Yokohama, Japan, November 16–18, 2015 Proceedings
123
Editors Joe Suzuki Osaka University Osaka Japan
Maomi Ueno The University of Electro-Communications Tokyo Japan
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-319-28378-4 ISBN 978-3-319-28379-1 (eBook) DOI 10.1007/978-3-319-28379-1 Library of Congress Control Number: 2015958747 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by SpringerNature The registered company is Springer International Publishing AG Switzerland
Preface
Over the last few decades, graphical models such as Bayesian and Markov networks have become increasingly popular artificial intelligence (AI) approaches. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), we explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented by discussions of practical considerations for applying graphical models in real-world settings, covering
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