Graph Structures for Knowledge Representation and Reasoning 4th Inte
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2015, held in Buenos Aires, Argentina, in July 2015, associated with IJCAI 2015
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Madalina Croitoru · Pierre Marquis Sebastian Rudolph · Gem Stapleton (Eds.)
Graph Structures for Knowledge Representation and Reasoning 4th International Workshop, GKR 2015 Buenos Aires, Argentina, July 25, 2015 Revised Selected Papers
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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
Madalina Croitoru Pierre Marquis Sebastian Rudolph Gem Stapleton (Eds.) •
•
Graph Structures for Knowledge Representation and Reasoning 4th International Workshop, GKR 2015 Buenos Aires, Argentina, July 25, 2015 Revised Selected Papers
123
Editors Madalina Croitoru LIRMM Montpellier Cedex 5 France Pierre Marquis CRIL-CNRS Lens France
Sebastian Rudolph Fakultät Informatik Technische Universität Dresden Dresden, Sachsen Germany Gem Stapleton University of Brighton Brighton UK
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-319-28701-0 ISBN 978-3-319-28702-7 (eBook) DOI 10.1007/978-3-319-28702-7 Library of Congress Control Number: 2015958918 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
Versatile and effective techniques for knowledge representation and reasoning (KRR) are essential for the development of successful intelligent systems. Many representatives of next-generation KRR systems are founded on graph-based knowledge representation formalisms and leverage graph-theoretic
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