Research and Development in Expert Systems XV: Proceedings of ES98, the Eighteenth Annual International Conference of the British Computer Society Specialist Group on Expert Systems, Cambridge, December 1998 PDF
Preview Research and Development in Expert Systems XV: Proceedings of ES98, the Eighteenth Annual International Conference of the British Computer Society Specialist Group on Expert Systems, Cambridge, December 1998
Research and Development in Expert Systems XV Springer London Berlin Heidelberg New York Barcelona Hong Kong Milan Paris Santa Clara Singapore Tokyo Roger Miles, Michael Moulton and Max Bramer (Eds) Research and Development in Expert Systems XV Proceedings of ES98/ the Eighteenth Annual International Conference of the British Computer Society Specialist Group on Expert Systems/ Cambridge/ December 1998 Springer Roger Miles, BSc, PhD XHP Consulting Ltd, Gloucester Michael Moulton, BSc, MBA, CEng Department of Accounting and Management Science, Portsmouth Business School, University of Portsmouth, Portsmouth Max Bramer, BSc, PhD, CEng Faculty of Technology, University of Portsmouth, Portsmouth lSBN-13: 978-1-85233-086-6 e-lSBN-13: 978-1-4471-0835-1 DOl: 10.1007/978-1-4471-0835-1 British Library Cataloguing in Publication Data Reasearch and development in expert systems XV : proceedings of Expert Systems 98, the eighteenth SGES international conference on knowledge based systems and applied artificial intelligence, Cambridge, December 1998 l.Expert systems (Computer science) -Congresses I.Miles, Roger ll.Moulton, Michael m.Bramer, M.A. (Max A.), 1948- 006.3'3 ISBN 1852330864 Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced. stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publishers. © Springer-Verlag London Limited 1999 Softcover reprint of the hardcover 1s t edition 1999 The use of registered names, trademarks etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant laws and regulations and therefore free for general use. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. Typesetting: Camera ready by contnbutors 34/3830-543210 Printed on acid-free paper TECHNICAL PROGRAMME CHAIRPERSON'S INTRODUCTION R.G.MILES XHP Consulting Ltd, Gloucester. This book is one of two volumes containing papers for presentation at the British Computer Society Expert Systems 98 conference. This is the annual conference of the BCS Specialist Group on Expert Systems and is in its 18th year. During its lifetime it has established itself as the premier Expert Systems conference in the UK. The conference is attracting an increasing number of papers world-wide and this year in excess of 70% were from research groups outside the UK. This volume includes all papers accepted for the Technical Stream of Expert Systems 98 and presented at the conference in December 1998. The papers within this stream present innovative, new research work. The companion volume, Applications and Innovations in Expert Systems VI, includes all papers accepted for the application stream of the conference. This stream has become the premier European conference on applications of Expert Systems. The papers accepted for presentation within the Technical Stream cover a broad range of research within Expert Systems and fit into four broad categories: ontological frameworks, knowledge base development, classifiers and neuro-fuzzy systems. The award for best Technical paper has been made to David McSherry, from the University of Ulster, for his paper entitled "Strategic Induction of Decision Trees". This paper describes an algorithm for decision-tree induction in which attribute selection can be explained in strategic terms providing support for incremental learning, problem solving and explanation. This paper is the clear award winner and the reviewers noted the breadth of application of the work. The Keynote Technical paper by David Goldberg from the University of Illinois, entitled "3 Lessons of Genetic Algorithms for Computational Innovation", proposes that Genetic Algorithms are a first order model of certain processes in human innovation. This volume once again shows the advanced techniques in general AI research which will in future be applied in several areas. ACKNOWLEDGEMENTS ES98 CONFERENCE COMMITTEE Professor Max Bramer, University of Portsmouth (Conference Chairperson) Dr Ian Watson, University of Salford (Deputy Conference Chairperson, Tutorial Co-ordinator) Dr Roger Miles, XHP Consulting Ltd. (Technical Programme Chairperson) Michael Moulton, University of Portsmouth (Deputy Technical Programme Chairperson) Dr Rob Milne, Intelligent Applications Ltd. (Application Programme Chairperson) Ann Macintosh, AlAI, University of Edinburgh (Deputy Application Programme Chairperson) TECHNICAL PROGRAMME COMMITTEE Roger Miles (Chair) Mike Moulton (Deputy Chair) Max Bramer Rick Magaldi Ian Watson TECHNICAL PROGRAMME REFEREES Steve Battle, University of the West of England Max Bramer, University of Portsmouth Claudia Eckert, Open University David Dodson, City University John Hunt, University of Wales, Aberstwyth Mark Keene, University of Dublin, Ireland John Kingston, University of Edinburgh Antonio Kreuger, Universitaet des Saarlandes, Germany Brian Lees, University of Paisley Rick Magaldi, British Airways pIc Roger Miles, XHP Consulting Ltd. Rob Milne, Intelligent Applications Ltd. Mike Mouton, University of Portsmouth John Nealon, Oxford Brookes University Barry O'Sullivan, University College Cork, Ireland Duska Rosenberg, BruneI University Jim Smith, University of the West of England Rob Smith, University of Alabama, USA Eva Stopp, Universitaet des Saarlandes, Germany Humphrey Sorensen, University College Cork, Ireland Peter Struss, Technical University of Munich, Germany Ian Watson, University of Salford CONTENTS TECHNICAL KEYNOTE ADDRESS 3 Lessons of Genetic Algorithms for Computational Innovation DE Goldberg ........................................................................................ 3 BEST TECHNICAL PAPER Strategic Induction of Decision Trees D. McSherry .......................................................................................... 15 SESSION 1: ONTOLOGICAL FRAMEWORKS Exploiting Knowledge Ontology for Managing Parallel Workflow Systems S. Aknine ............................................................................................... 29 A Generic Ontology for Spatial Reasoning F. Coenen, P. Visser ............................................................................. 44 Knowledge Modelling for a Generic Refinement Framework R. Boswell, S. Craw ............................................................................... 58 SESSION 2: KNOWLEDGE BASE DEVELOPMENT CG-SQL: A Front-End Language for Conceptual Graph Knowledge Bases S. Coulondre ......................................................................................... 77 Constraint-Based Knowledge Acquisition and Verification for Planning R. Barruffi, E. Lamma, M. Milano, R. Montanari, P. Mello ..................... 96 Coping with Poorly Understood Domains: The Example of Internet Trust A Basden, J.B. Evans, D.W Chadwick, A Young ............................... 114 SESSION 3: Classifiers Pruning Boosted Classifiers with a Real Valued Genetic Algorithm S. Thompson ......................................................................................... 133 On Rule Interestingness Measures AA Frietas ............................................................................................ 147 MVC -A Preprocessing Method to deal with Missing Values A Ragel , B. Cremilleux ........................................................................ 159 SESSION 4: Neuro-Fuzzy Approaches Alarm Analysis with Fuzzy Logic and Multilevel Flow Models F. Dahlstrand ......................................................................................... 173 Learning Full Pitch Variation Patterns with Neural Nets T. Zhu, W Gao, C.x. Ling ..................................................................... 189 A Neural Network Based Approach to Objective Voice Quality Assessment R. T. Ritchings, G. V. Conroy, M.A. McGillion, G.J. Moore, N. Slevin, S. Winstanley and H. Woods ................................................................. 198 REVIEW PAPER Case-Based Reasoning is a Methodology not a Technology I. Watson ............................................................................................... 213 Author Index ........................................................................................ 225 TECHNICAL KEYNOTE ADDRESS 3 Lessons of Genetic Algorithms for Computational Innovation 1 David E. Goldberg Department of General Engineering University of Illinois at Urbana-Champaign Urbana, Illinois 61801 [email protected] Reprinted from: Babovic, Vladan & Lars Christian Larsen, Hydroinformatics '98 - Proceedings of the Third International Conference on Hydroinformatics, Copenhagen, Denmark, 24-26 August 1998. 1998. C.1530 pp., Hfl.276IUS$140.00/GBP92.00. A.A.Balkema, P.O. Box 1675, Rotterdam, Netherlands (e-mail: [email protected]). Introduction For some time, I have been struck by the connection between the mechanics of innovation and genetic algorithms (GAs}--search procedures based on the mechanics of natural selection and genetics. In this short paper, I explore those connections by invoking the fundamental metaphor of innovation as an explanation for GA power of effect. Thereafter, I reverse the argument, by setting out to construct competent GAs-GAs that solve hard problems quickly, reliably, and accurately-through a combination of effective (I) design methodology, (2) design theory, and (3) design. While, we won't have the opportunity to review the technical lessons in detail, the abstract does examine three crucial qualitative issues: (1) the key race between selection and the innovation operators, (2) the idea of a control map that helps us understand the genetic algorithm's 1 A considerably extended version of this argument will appear in "The Race, the Hurdle, and the Sweet Spot: Lessons from Genetic Algorithms for the Automation of Design Innovation and Creativity," in P. Bentley (Ed.), Evolutionary Design by Computers, Academic Press. R. Miles et al. (eds.), Research and Development in Expert Systems XV © Springer-Verlag London Limited 1999
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