Lecture Notes in Artificial Intelligence

Subseries of Lecture Notes in Computer Science

Edited by J. G. Carbonell and J. Siekmann

Lecture Notes in Computer Science Edited by G. Goos, J. Hartmanis and J. van Leeuwen

1416

Angel Pasqual del Pobil Jos6 Mira Moonis Ali (Eds.)

Tasks and Methods in Applied Artificial Intelligence

11 th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-98-AIE Benichssim, Castell6n, Spain, Junel-4, 1998 Proceedings, Volume II

Springer

Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA J6rg Siekmann, University of Saarland, Saarbrticken, Germany

Volume Editors

Angel Pasqual deI Pobil Department of Informatics, Jaume-I University Campus Penyeta Roja, E-12071 Castell6n, Spain E-mail: pobil @inf.uji.es

Jos6 Mira Departamento de InteligenciaArtificial, Facultad de Ciencias Universidad Nacional de Educaci6n a Distancia Senda del Rey, s/n, E-28040 Madrid, Spain E-mail: jmira@dia.uned.es

Moonis All Department of Computer Science, SouthwestTexas State University San Marcos, TX 78666-4616, USA E-mail: ma04@swt.edu

Cataloging-in-Publication Data applied for

Die Deutsche Bibliothek ~ ClP-Einheitsaufnahme

International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems <II , 1998, Benicasim; Castell~n de It Pinna>: 11 th International Conference on Industrial and Engineering Applications o f Artificial Intelligence and Expert Systems : Benie~assim, Casteil~n, Spain, June 1 - 4, i998 ; proceedings / IEA-98-A1E - Berlin ; Heidelberg ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara ; Singapore ; Tokyo : Springer

Vol. 2. Tasks and methods in applied artificial intelligence / Angel Pasqual de,/Pobil ... (od.). - 1998

(Lecture notes in computer science ; Vot. 1416 : Lecture notes in artificial intelligence) ISBN 3-540-64574-8

CR Subject Classification (1991): 1.2, J.2, J.6

ISBN 3-540-64574-8 Springer-Verlag Berlin Heidelberg New York

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Preface

Nowadays, it is generally accepted that the aim of Applied Artificial Intelligence is to render computational a large portion of non-analytical human knowledge. To attain this end, we need first to build knowledge-level models of analysis and synthesis tasks in scientific and technical domains, such as those performed daily by human experts in fields such as medical diagnosis, design in civil or telecommunication engineering, architecture, flexible manufacturing, or tutoring. Then, these models have to be transformed in such a way that their entities and relations can be linked to the primitives of a programming language and, finally, produce a program and continue with the usual phases in software engineering (validation, evaluation, and maintenance).

This purpose, that seems to be clear, has suffered since its origins in 1956, from a lack of methodology and foundations. That is, there has been an excessive hurry to develop applications (expert systems) without the technical and methodological support available to other engineering disciplines --those dealing with matter or energy-- having been established. This is the reason why the advancement of Knowledge Engineering has not been as robust as expected.

Fortunately, interest in methodology and foundations has grown in recent years, commencing by Clancey and Chandrasekaran's proposals about generic tasks aiming at capturing recurrent abstractions in human knowledge modeling. Then, efforts have been made to build libraries of problem-solving methods to develop these tasks by decomposing them up to primitive level and completing these tasks and methods with ontologies and domain knowledge models together with a set of assumptions about implicit representations for each method and about the method's assumptions which are implicit in each domain model. These three basic concepts --tasks, method, and domain--, along with the underlying pursuit of designing reusable components, have characterized most of methodological developments around KADS, CommonKADS, and PROTt~Gt~, for instance.

The scope and topics included in the Call for Papers of the Eleventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-98) were compiled within this spirit of concern about sound foundations and methodology, as well as with the explicit acknowledgment of the necessity of developing efficient procedures to make the models operational. As a result of this call, 291 contributed and invited papers were submitted from 41 countries; the program committee selected 187 among them, after conscientiously considering the reviews provided by at least two referees per paper. We believe that the significant increase in the number of submitted papers, with respect to recent conferences, is a symptom of a maturing interest within the AI community towards fundamental issues relevant to well-founded and robust applications in the real world.

We are pleased to present, as program chairs and editors of these two volumes, a final version of the accepted papers incorporating the reviewers' comments. We have arranged their contents basically following the topic list included in the Call for Papers, adding some additional topics which received special attention as a result of being the subject of invited sessions. The first volume entitled Methodology and Tools in Knowledge-Based Systems, is divided into four main parts and includes the

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contributions having a basic and methodological nature, along with those concerning knowledge modeling, formal tools, and generic tasks of analysis in applied AI. There are sections on fuzzy knowledge representation and inference, qualitative reasoning, evolutionary computing, and multiagent systems, among others.

One of the most frequent deficiencies in the majority of methodological developments lies in ignoring the conclusive step about how to render the models operational with the final result of an implemented system. We believe that this fact accounts for a considerable lack of credibility towards AI among researches on the outside, who feel that it has failed in that it has not made enough inroads into real- world applications. Consequently, AI researchers are sometimes seen as just blowing smoke. It is still common to find journal articles that do not support claims on rigorous experimental evidence or that only show solutions to toy problems by way of validation.

In the second volume, with the title Tasks and Methods in Applied Artificial Intelligence, we have included the contributions dealing with aspects that are more directly relevant to application development. These contributions are grouped into five parts: generic tasks of synthesis and modification, machine learning, applied AI and Knowledge-Based Systems in specific domains, and validation and evaluation criteria.

The editors are also aware of the grand challenges for AI concerning artificial behavior for agents that have to deal with the real world through perception and motor actions. Nowadays, there is an enormous lack of balance between existing AI systems in some aspects of their competence. Whereas in some formal microworlds AI systems have reached the highest human level of competence - - the recent success of chess-playing systems being a paradigmatic example--, or there are knowledge-based systems exhibiting human expert competence in narrow technical domains such as medical diagnosis, etc., few systems exist surpassing the competence of a cockroach, for instance, in moving around pursuing a goal in an unstructured world. This enormous distance between pure abstract intellectual tasks at one end, and those that involve sensorimotor interaction with the physical world at the other, calls for an emphasis on research on robotic agents.

Since the current state of affairs is partly due to the Turing vision of a disembodied, abstract, symbol-processing intelligence, new proposals --such as those put forward by Harnad or Brooks-- are worth consideration. Robotic capacities including the ability to see, grasp, manipulate, or move have been added to an extended version of the Turing test. The symbol grounding problem has been approached by the physical grounding hypothesis: grounding a system's representations in the physical world via sensory devices with the result of emergent functionalities. Taking the biological paradigm seriously implies building on top of an integrated and distributed sensorimotor system, since the coordination of our movement is done mainly in an unconscious way, relying on perception without central processors coming into play. Neural networks have proven to be an adequate paradigm for approaching this kind of problem as well as others at the subsymbolic level. We believe that the connectionist and symbolic perspectives to AI should be taken as mutually supporting approaches to the same problems, rather than as competitive areas, as is often the case. Hybrid systems integrating both perspectives appear to be the right track to follow.

This emphasis on perception and robotics has obtained a satisfactory response in terms of the number of submitted papers, as compared with previous conferences.

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Consequently, a section on perception is included in Volume I, and in Volume II more than 20 papers can be found in sections devoted to perceptual robotics, robot motion planning, and neurofuzzy approaches to robot control.

The papers included in this volume were presented at IEA/AIE-98 which was held in Benichssim, Castell6n, Spain on June 1-4, 1998. The event was sponsored by the International Society of Applied bltelligence - -which promotes this conference series--, Universidad Jaume I de Castell6n - - the hosting institution-- and Universidad Nacional de Educaci6n a Distancia, in cooperation with several international associations such as AAAI, ACM/SIGART, ECCAI, and AEPIA, among others. Support for this event has been provided by Fundaci6 Caixa Castell6- Bancaixa, Ministerio de Educaci6n y Ciencia, Fundaci6 Universitat Empresa of the Universidad Jaume I, and Silicon Graphics Computer Systems.

We would like to express our sincere gratitude to the members of the organizing and program committees, to the reviewers, and to the organizers of invited sessions for their invaluable effort in helping with the preparation of this event. Thanks also to the invited speakers, Michael Brady and Bob J. Wielinga, with particular gratitude to Roberto Moreno-Dfaz, for their original papers given as plenary lectures and appearing in this book. Thanks also to Moonis Ali, president of ISAI and IEA/AIE-98 general chair, for his constant support. The collaboration of the Technical Committee on Robot Motion and Path Planning of the IEEE Robotics and Automation Society deserves a special mention, as well as Toshio Fukuda, president of this society, for his help in the review process. Also, thanks to Springer-Verlag and particularly to Alfred Hofmann for an already long and fruitful collaboration with us. We sincerely thank all authors for making the conference and this book possible with their contributions and participation.

Finally, the editors would like to dedicate this book to the memory of Ntiria Piera, who promoted research on qualitative reasoning across Spain and Europe and could not see by herself the success of her last organized session, since she had to move to her definitive dwelling.

The theme for the 1998 conference was New Methodologies, Knowledge Modeling and Hybrid Techniques. Our focus has been on methodological aspects in the development of KBS's, knowledge modeling, and hybrid techniques that integrate the symbolic and connectionist perspectives in AI applications. The global assessment of the contributions contained in these two volumes is reasonably positive. They give a representative sample of the current state of the art in the field of Applied Artificial Intelligence and Knowledge Engineering and they clearly illustrate which problems have already been solved or are on the way to being solved and which still present a challenge in the serious enterprise of making Applied Artificial Intelligence a science and an engineering discipline as unequivocal and robust as physics or matter and energy engineering. We hope that these volumes will contribute to a better understanding of these problems and to expedite the way to their solution for the well-being of humankind with the advent of the third millennium.

Angel Pasqual del Pobil Jos6 Mira Mira March 1998

Table of Contents, Vol. lI

1 Synthesis Tasks

NEUROCYBERNETICS, CODES A N D C O M P U T A T I O N . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 ROBERTO MORENO D1AZ

THE G R A N D C H A L L E N G E IS CALLED: ROBOTIC INTELLIGENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5 ANGEL P. DEL POB1L

Spatial, Temporal and Spatio-Temporal Planning and Scheduling

A PROGRESSIVE HEURISTIC SEARCH A L G O R I T H M FOR THE CUTFING STOCK

P R O B L E M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 E. ONAINDIA, F. BARBER, V. BOITI, C. CARRASCOSA, M.A. HERNADEZ, M. REBOLLO

DISCOVERING TENfi:~)RAL RELATIONSHIPS IN D A T A B A S E S OF N E W S P A P E R S . . . . . . . . . 36 RAFAEL BERLANGA LLA VOR1, M.J. ARAMBURU, F. BARBER

GENERIC CSP TECHNIQUES FOR T H E JOB-SHOP P R O B L E M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 6 JA VIER LARROSA, PEDRO MESEGUER

A FAST A N D EFFICIENT SOLUTION TO T H E CAPACITY ASSIGNMENT P R O B L E M

USING DISCREFIZED LEARNING A U T O M A T A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 B. JOHN OOMMEN, T. DALE ROBERTS

Motion Planning for Robots

USING OXSIM FOR PATH PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 STEPHEN CAMERON

MULTI-DIRECFIONAL SEARCH WITH G O A L SWITCHING FOR ROBOT PATH

PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 DOMIN1K HENRICH, CHRISTIAN WURLL, HEINZ WORN

A N A L Y T I C A L POTENTIAL FIELDS A N D C O N T R O L STRATEGIES FOR MOTION

PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 SEUNG-WO0 KIM, DANIEL BOLEY

EXACT GEOMETRY A N D ROBOT MOTION PLANNING: S P E C U I A T I O N S ON A F E W

N U M E R I C A L EXPERIMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 CLAUDIO MIROLO, ENRICO PAGELLO

A N EVOLUTIONARY A N D L O C A L SEARCH A L G O R I T HM FOR PLANNING T W O

MANIPULATORS MOTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 M.A RIDAO, J. R1QUELME, E.F. CAMACHO, MIGUEL TORO

A GENETIC A L G O R I T H M FOR ROBUST MOTION PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I 15 DOMINGO GALLARDO, OTTO COLOMINA, FRANCISCO FLOREZ, RAMON RIZO

C O O R D I N A T E D MOTION O F T W O ROBOT A R M S FOR R E A L APPLICATIONS . . . . . . . . . . . 122 M. PEREZ-FRANCISCO, ANGEL P. DEL POB1L, B. MART[NEZ-SALVADOR

×

A LOW-RISK APPROACH TO MOBILE ROBOT PATH PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2

MAARJA KRUUSMAA, BERT1L SVENSSON

System Configuration

GENERATING HEURISTICS TO CONTROL CONFIGURATION PROCESSES . . . . . . . . . . . . . . . 142 BENNO STEIN

2 Modification Tasks

Knowledge-Based Control Systems

VALUING THE ~_~EXIBIL1TY OF FLEXIBLE MANUFACTURING SYSTEMS WITH

FAST DECISION RULES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 MARKUS FEURSTEIN, MARTIN NATTER

OPTIMAL PERIODIC CONTROL WITH ENVIRONMENTAL APPLICATION . . . . . . . . . . . . . . . . 163 VLADIM1R NIKUL1N

A CENTRALISED HIERARCHICAL TASK SCHEDULER FOR AN URBAN TRAF~7C CONTROL SYSTEM BASED ON A MULTIAGENT ARCHITECTURE . . . . . . . . . . . . . . . . . . . . . . . . . 173 L.A. GARC[A, FRANCISCO TOLEDO

A DIRECT ITFRATION MEFHOD FOR GLOBAL DYNAMIC CONTROL OF REDUNDANT MANIPULATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 WE1HA1CHEN, ZHEN WU, QIX1AN ZHANG, JIAN LI, LUYA LI

DESIGN OF SHIP-BOARD CONTROL SYSTEM BASED ON THE SOFT COMPUTING

CONCEPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 YU.I. NECHAEV, YU L. S1EK

Dynamic Systems Supervision EXPERT DIAGNOSTIC USING QUALITATIVE DATA AND RULE-BASED INFERENTIAL REASONING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200 JOAQU1M MELENDEZ-FR1GOLA, JOAN COLOMER-LLINAS, JOSEP LLU[S DE LA ROSA- ESTEVA, ORLANDO CONTRERAS

QUALITATIVE EVENT-BASED EXPERT SUPERVISION-PART 1: METHODOLOGY . . . . . . 210 FLAVIO NEVES JUNIOR, JOSEPH AGUILAR-MARTIN

QUALITATIVE EVENT-BASED EXPERT SUPERVISION-PART 2: DISTILLATION STPuRT-UP CONDITION MONITORING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 FLAVIO NEVES JUNIOR, JOSEPH AGUILAR-MARTIN

ALARM PROCESSING AND RECONNGURATION IN POWER DISTRIBUTION

SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230 MAR1E-ODILE CORDIER, JEAN-PAUL KRIV1NE, PHILIPPE LABORIE, SYLVIE THI~BAUX

BEHAVIORAL INTF~PREFATION ACCORDING TO MULTIMODELING REPRESENTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 FAKHER ZOUAOUI, RENAUD THETIOT, MICHEL DUMAS

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Intelligent Supervision

AN INTELLIGENT AGENT TO AID IN UNIX SYSTEM ADMINISTRATION . . . . . . . . . . . . . . . . . . 252 J.H. HAML1N, WALTER D. POTI~R

PROCESS OPTIMISATION IN AN INDUSTRIAL SUPERVISION SUPPORT SYSTEM . . . . . 261 HERNAN VILLANUEVA, HARMEET LAMBA

Predictive Control Systems

MIMO PREDICTIVE COIVI'ROL OF TEMPERATURE AND HUMIDITY INSIDE A GREENHOUSE USING SIMULATED ANNEALING (SA) AS OFFIMIZER OF A MULTICRITERIA INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 JUAN S. SENENT, MIGUEL A. MART[NEZ, XAVIER BL4SCO, JAVIER SANCHIS

Perceptual Robotics

STEREO VISION-BASED OB~I'ACI~.; AND I:REE SPACE DETECTION IN MOBILE ROBOTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 J.M. SANCHIZ, A. BROGGI, F1LIBFRTO PLA

TOPOLOGICAL MODELING WrI'l t FUZZY PETRI NETS FOR AUTONOMOUS MOBILE ROBOTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290 J. DE LOPE, DAR[O MARAVALL, JOSt~ G. ZATO

SUPERVISED REINFORCEMENT LEARNING: APPLICATION TO A WALL FOLLOWING BEHAVIOUR IN A MOBILE ROBOT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 R. 1GLES1AS, C. V, REGUE1RO, J, CORREA, S. BARRO

A COMMUNICATION PROTOCOL FOR CLOUDS OF MOBILE ROBOTS . . . . . . . . . . . . . . . . . . . . 310 MIGUEL Sti.NCHEZ LOPEZ, METRO MANZON1

EVOLVING NEURAL CONFROLUERS FOR TEMPORALLY DEPENDENT

BEHAVIORS IN AUTONOMOUS ROBOTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 JOSE SANTOS, RICHARD J. DURO

GA-BASED ON-LINE PATH PLANNING FOR SAUVIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 KAZUO SUGIHARA

INCREMENTAL BUILDING OF A MODEL OF ENVIRONIVIENq" IN THE CONTEXT OF THE McCL~LOCH-CRAIK'S FUNCTIONAL ARCHITECTURE FOR MOBILE ROBOTS... 339 J. ROMO, F. DE LA PAZ, J. MIRA

TELEROBOTIC SYSTEM BASED ON NATURAL LANGUAGE AND COMPbTER VISION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 RAUL A,£4R[N, G. RECATALA, PEDRO J. SAA'Z, J.M. I]VESTA, ANGEL P. DEL POBIL

ROBUST REGION-BASED STEREO VISION TO BUILD ENVIRONMENT MAPS FOR

ROBOTICS APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 M. ANGELES LOPEZ, FIL1BERTO PLA

Fuzzy and Neurofuzzy Approaches to Robot Control

A NEW ON-LINE STRUCTURE AND PARAMETER LEARNING ARCHITECTURE FOR FUZZY MODELING, BASED ON NEURAL AND FUZZY TECHNIQUF~ . . . . . . . . . . . . . . . . . . . . . . 375 SPYROS G. TZAFESTAS, KONSTANTINOS C. ZIKIDIS

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AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM(ANFIS) APPROACH TO CONTROL OF ROBOTIC MANIPULATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 Aid ZILOUCHIAN, DAVID W. HOWARD, TIMOTHY JORDAN1DES

Program Reuse

MANAGING THE USAGE EXPERIENCE IN A LIBRARY OF SOFFWARE COMI~NENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393 PEDRO A. GONZ.A~LEZ-CALERO, MERCEDES GOMEZ-ALBARR,,~AV, CARMEN FERNANDEZ-CHAMIZO

WHAT CAN PROGRAM SUPERVISION DO FOR PROGRAM RE-USE? . . . . . . . . . . . . . . . . . . . . . . 403 MON1QUE THONNAT, SABINE MOISAN

USING ARTIFICIAL INTFJ J .IGENCE PLANNING TECHNIQUES TO AUTOMATICALLY RECONFIGURE SOFTWARE MODULES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 STEVE CHIEN, FOREST FISHER, HELEN MORTENSEN, EDISANTER LO, RONALD GREELEY, ANITA GOVINDJEE, TARA ESTLIN, XUEMEI WANG

USE OF KNOWLEDGE-BASED CONTROL FOR VISION SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . 427 C. SHEKHAR, SABINE MOISAN, R. VINCENT, P. BURLINA, R. CHELLAPPA

3 Machine Learning

Machine Learning Applications: Tools and Methods

SOLUTION FOR A LEARNING CONFIGURATION SYSTEM FOR IMAGE

PROCESSING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 CLAUS-E. LIEDTKE, HE1KO M(INKEL, URSULA ROST

MACHINE LEARNING USEFULNESS RELIES ON ACCURACY AND SELF- MAINTENANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 OSCAR LUACES, JAIME ALONSO, ENRIQUE A. DE LA CAL, JOSE RANILLA, ANTONIO BAHAMONDE

IMPROVING INDUCI'IVE LEARNING IN REAL-WORLD DOMAINS THROUGH THE IDENTIFICATION OF DEPENDENCIES: THE TIM FRAMEWORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . 458 JUAN PEDRO CARA~A-VALENTE, CESAR MONTES

FROM THE NFAREST NEIGHBOUR RULE TO DECISION TREES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469 J.S. S,,~NCHEZ, FILIBERTO PLA, F.J. FERRI

A NEW SELF-ORGANIZING STRATEGY BASED ON ELASTIC NETWORKS FOR

SOLVING THE EUCLIDEAN TRAVELING SALESMAN PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 LUIZ SATORU OCHI, NELSON MACULAN, ROSA MARIA V1DEIRA F1GUEIREDO

Inductive and Deductive Strategies

AN INDUCI'IVE LEARNING SYSTEM FOR RATING SECURITIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 488 MEHDI R. ZARGHAM

×111

Case-Based Reasoning

TECHNIQUES AND KNOWLEDGE USH) FOR ADAVFATION DURING CASE-BASED

PROBLEM SOLVING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 WOLFGANG WILKE, RALPH BERGMANN

CASE-BASE MAINTENANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507 BARR Y SMYTH

CBR: STRENGTHS AND WEAKNESSES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517 P.,iADRA1G CUNNINGHAM

IS CBRA TECI-hNOIX)GY OR A METHODOLOGY? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525 IAN WATSON

AN EFFICIENT APPROACH TO ITERATIVE BROWSING AND RETRIEVAL FOR

CASE-BASED REASONING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535 IGOR JUR1SICA, JAN1CE GLASGOW

CASE BASED APPROACH TO THE CONSTRUCTION OF A COAL MOLECULAR STRUCfURE MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 KOJI TANAKA. TAKENAO OHKA WA, NORIHISA KOMODA

Learning Advances in Neural Networks

CONSTRUCI'ING HIGHER ORDER N~URONS OF INC~J~StNG COMPLEXITY IN CASCADE NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 N.K. TREADGOLD, T.D, GEDEON

INTERPRETABLE NEURAL NETWORKS WITH BP-SOM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 TON WE1JTERS, ANTAL VAN DEN BOSCH

REFERENCE PATTERN WEIGHT INITIALIZATION FOR EQUALIZATION . . . . . . . . . . . . . . . . . . 574 MIKKO LEHTOKANGAS

AUI'OASSOCIATIVE N E ~ NETWORKS FOR FAULT DIAGNOSIS IN SEMICONDUCFOR MANUFACFURING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 582 LUIS d. BARRIOS, L1SSEITE LEMUS

SUPERVISED TRAINING OF A NEURAL NETWORK FOR CLASSIFICATION VIA SUCCESSIVE MODIFICATION OF THE TRAINING DATA - AN EXPERIMF2qTAL STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 593 MAYER ALADJEM

AN UNSUPERVISED TRAINING CONNECI'IONIST NETWORK WITH LATFJ~AL INHIBITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 LEVENTE KOCSIS, NICOLAE B. SZIRB1K

TEMtZ~RAL DIFFERENCE LEARNING IN CHINFSE CHESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612 THONG B. TRINH, ANWER S. BASHI, NIKH1L DASHPANDE

XIV

4 Applied Artificial Intelligence and Knowledge-Based Systems in Specific Domains

APPLYING OBJECT IX)GIC PROGRAMMING TO DESIGN COMPUTER STRATEGIES

IN GENE SCANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619 OSCAR COLTELL, JOSF. M. ORDOVAS

Multimedia

AUTOMATIC SI'ORING AND RUFR1EVAL OF LARGE COLLECTIONS OF IMAGES . . . . . . 628 AGOSThVO POGGI, G1ANLUCA GOLINELL1

ALTERNATIVE COMMUNICATION INTERFACE FOR SEVERELY HANDICAPPED PEOPLE BASED ON A MULTIMEDIA HUMAN-COMPIYI'ER INTERACTION SYSTEM... 638 OSCAR COLTELL, JAVIER LLACH, PEDRO SANZ, CARMEN RU[Z, DAVID CARRERES

Human-Computer Interaction

PERSONAl JZING MUSEUM EXHIBITION BY MEDIATING AGENTS . . . . . . . . . . . . . . . . . . . . . . . . 648 RIEKO KADOBAYASHI, KAZUSHI NISHIMOTO, YASUYUKI SUMI, KENJI MASE

A COMBINED PROBABILISTIC FRAMEWORK FOR LEARNINIG GESTURES AND

ACFIONS658 FRANCISCO ESCOLANO RUIZ, MIGUEL CAZORLA, DOMINGO GALLARDO, FARAON LLORENS, ROSANA SATORRE, RAMON RIZO

DESIGNING WORKSPAC~ TO SUPPORT COLLABORATIVE LEARNING . . . . . . . . . . . . . . . . . 668 BEATRIZ BARROS, FELISA VERDEJO

Decision Support Systems

DEVELOPMENT OF DECISION SUPI~RT SYSTEM FOR INTEGRATED WATER MANAGEMENT IN RIVER BASINS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 678 ZONGXUE XU, K. ITO, K. JINNO, T. KOJIR1

AN APPLICATION OF" AN AI MEFHODOUN3Y TO RAILWAY INTERLOCKING

SY STEMS USING COMPUTER ALGEBRA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687 EUGENIO ROANES-LOZANO, LUIS M. LAITA, EUGEN10 ROANES-MAC[AS

INTELLIGENT INTERPRETATION OF STRENGTH DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697 FERNANDO ALONSO AMO, JOSE MARIA BARREIRO, JUAN PEDRO CARA~A-VALENTE, CESAR MONTES

HADES - A KNOWLEDGE-BASED SY STEM FOR MESSAGE INTERPREFATION AND

SITUATION DETERMINATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 707 JOACHIM BIERMANN

Tutoring Systems

WORK IN PROGRESS: VISUAL SPECIFICATION OF KNOWLEDGE BASES . . . . . . . . . . . . . . . 717 TANYA GA VRILOVA, A. VOINOV

WEBTUTOR, A KNOWLFGDE BASED SYSTEM FOR EVALUATION AND TUTORSHIP . . . . . . . . . . . . . . . . . . . . . . . . : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727 SERGIO CORONADO, A. GARC[A-BELTR.,~, J.A. JAEN, R. MART[NEZ

XV

CONTROL KNOWLEDGE AND PEDAGOGICAL ASPECTS OF THE GET-BITS

MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3 5 LJUBOMIR JER1NIC, VLADAN DEVEDZIC, DANIJELA RADOVIC

Connectionist and Hybrid AI Approaches to Manufacturing

IMPROVING BEHAVIOR ARBITRATION USING EXPLORATION AND DYNAMIC

PROGRAMMING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745 MOHAMED SALAH HAMDI, KARL KAISER

AGENT BASED ARCHITECFURES FOR MASTERING CHANGES AND

DISTURBANCES IN MANUFACTURING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 5 5 LASZLO MONOSTOR1, BOTOND K,~DAR

SOFT COMPUTING AND HYBRID AI APPROACHES TO INTELLIGENT

MANUFACTURING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 6 5 LASZLO MONOSTOR1, JOZSEF HORNYAK, CSABA EGRESITS, ZSOLT JANOS VIHAROS

COMPARING SOFT COMPUTING METHODS IN PREDICTION OF

MANUFACTURING DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 7 5 ESA KOSK1MJ{K1, JANNE GOOS, PETR1KONTKANEN, PETRI MYLLYMJ(KI, HENRY TIRRI

Modeling and Simulation of Ecological/Environmental Systems

TOWARDS AN EMERGENCE MACHINE FOR COMPLEX SYSTEMS SIMULATIONS .. . . 785 PIERRE MARCENAC, REMY COURD1ER. ST~PHANE CALDERONI, J. CHRISTOPHE SOULIF,

SPACE MODELS AND AGENT-BASED UNIVERSE ARCHrFECTURES . . . . . . . . . . . . . . . . . . . . . . 795 JEAN-PIERRE TREUIL

MOBIDYC, A GENERIC MULTI-AGENTS S I M I B ~ T O R FOR MODELING

P O P ~ T I O N S DYNAMICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 805 VINCENT GINOT. CHRISTOPHE LE PAGE

DEVELOPMENT OEAN ECOLOGICAL DEC[S1ON SUPPORT SYSTEM . . . . . . . . . . . . . . . . . . . . . . 815 FRITS" VAN BEUSEKOM, FRANCES BRAZIER. P1ET SCHIPPER, JAN TREUR

CORMAS: COMMON-F'OOL RESOURCES AND MULTI-AGENTS SYSTEMS . . . . . . . . . . . . . . 826 FRANCOIS BOUSQUET, INNOCENT BAKAM, HUBERT PROTON, CHRISTOPHE LE PAGE

Reports on Real Applications with Significant Findings

DYNAMIC PROCESS MODELLING AND COMMUNICATION IN ENVIRONMENT

INFORMATION SYSTEMS OF THE THIRD GENERATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 838 AXEL GROHMANN, ROLAND KOPETZKY

LANDCAPE: A KNOWLEDGE-BASED SYSTEM FOR VISUAL LANDSCAPE

ASSESSMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 849 RODRIGO MART[NEZ-BEJAR, FERNANDO MART[N-RUBIO

DAILY PARKING OF SUBWAY VEHICLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 857 BOUTHEINA LASSOUED, RYM M'HALLAH

THE ARTIFICIAL NEURAL NETWORKS IN COSMIC RAY PHYSICS EXPERIMENT;

I.TOTAL MUON NUMBER ESTIMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 TADEUSZ WIB1G

XVI

5 Validation and Evaluation Criteria

STATIC C~TERIA FOR FUZZY SYSI'EMS QUALITY EVALUATION . . . . . . . . . . . . . . . . . . . . . . . . 877 ESTEVE DEL ACEBO, ALBERT OLLER, JOSEP LLUIS DE LA ROSA, ANTON1LIGEZA

WALLAID: A KNOWl ~E13GE-BASFJ) SYSTEM FOR THE SELECI'ION OF EARTH RETAINING WALLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 888 IAN G.N. SMITH, ANDREW OLIVER, JOHN OL1PHANT

A MODULAR AND PARAMETRIC STRUCI'URE FOR THE SUBSTITUTION REDESIGN OF POWER PLANTS CONTROL SY STEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 896 A. PARKA, M. R1NCON, J.R. ,itLVAREZ, J. MIRA, A. DELGADO

S i m u l a t i o n

A POLYSYNAFFIC PLANAR ~ NETWORK AS A MODEL OFTHE MYENTERIC NERVOUS PLEXUS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 907 R.N. MIFTAKOV, J. CHRlSTENSEN

SELECTION OF NUMERICAL METHODS IN SPECIFIC SIMULATION APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 918 BENNO STEIN, DANIEL CURATOLO

FU2ZY ADAPI'ATIVE CONTROL OFTHE HIGHLY NONLINEAR HEAT-F~CHANGE PLANT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 928 IGOR ~KRJANC, DRAGO MATKO

A u t h o r I n d e x . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 939

Table of Contents, Vol. I

1 Methodological Aspects

KNOW1 .ELSE TECHNOLOGY: MOVING INTO THE NEXT IvIlI I .FTNIUM . . . . . . . . . . . . . . . . . . . . . . . . 1 B.J. WIELINGA, A.TH. SCHREIBER

IN SEARCH OFA COMMON STRUCTURE UNDERLYING A REPRESENTATIVE SE~ OF GENERIC TASKS AND IVlETHODS: THE HIERARCHICAL CLASSIFICATION AND THERAPY PLANNING CASES STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 J.C. HERRERO, J. MIRA

THEORY OF CONSTRUCT1BLE DOMAINS FOR ROBOTICS: WHY? . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 MARTA FRAIVOVA, MONIA KOOLI

INTELLIGENT SYSTEMS MUST BE ABLE TO MAKE PROGRAMS AUTOMATICALLY FOR ASSURING THE PRACFIC_tkHTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 7 TAKUMI AIDA, SETSUO OHSUGA

TOWARDS A KNOWI .EV~E-LEVI~ MODEL FOR CONCURRENT DESIGN . . . . . . . . . . . . . . . . . . . 57 ROBIN BARKER, ANTHONY MEEHAN, IAN TRANTER

MULTIAGH'4T AI IMPLEMENTATION TEL-'HNIQUES: A NEW SOFTWARE H'4GIN~ERLNG TREN~D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 8 CYRUS F. NOURANI

IN ORivIATION SYSTEMS INTEGRATION: SOME PRINCIPLES AND IDEAS . . . . . . . . . . . . . . . . 7 9 NAHLA HADDAR, FM'EZ GARGOURI, ABDEb~4AJID BEN H~tADOU, CHARLES FRANCOIS DUCATEAU

2 Knowledge Modeling

AN EMERGENT PARADIGM FOR EXPERT RESOURCE MANAGEMENT SYSTEMS . . . . . . . 89 SWAMY KUITI, BRIAN GARNER

MODEl JNG METHOD FOR USING LARGE KNOWLEDGE BASES . . . . . . . . . . . . . . . . . . . . . 102 WATARU IKEDA, SETSUO OHSUGA

INTEGRATION OF FORMAL CONCEPT ANALYSIS IN A KNOWI .EI3GE-BASED ASSISTANT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 BALTASAR FE~r~EZ-MANJON, ANTONIO NA VARRO, JUAN 114. CIGARRAN, ALFREDO FERNANDEZ-VALMAYOR

KNOWLEDGE MODEI .ING OF PROGRAM SUPERVISION TASK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 MAR MARCOS, SABINE MOISAaV, ANGEL P. DEL POB1L

QUADRI-DIMENSIONAL INTERPRETATION OF SYLLOGISTIC INFERENTIAL PROCESSES IN FOLYVAI .ENT LOGIC, WITH A VIEW TO STRUCTURING CONCEPTS AND ASSERTIONS FOR RE, A L I Z ~ G THE UNIVERSAL KNOW[ EI'X3E BASIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 ION L MtRITA

XVIII

3 Formal Tools

COMPLEXITY OF PRECEDENCE GRAPHS FOR ASSEMBLY AND TASK PLANNING . . . . 149 JOA O ROCHA, CARLOS RAMOS, Z1TA VALE

A MONTE CARLO ALGORITHM FOR THE SATISFIABILITY PROBLEM . . . . . . . . . . . . . . . . . . . 159 HABIBA DRIAS

Fuzzy Knowledge Representation and Inference

APPLYING THE PROPOSE&REVISE STRATEGY TO THE HARDWARE-SOFTWARE PARTITIONING PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 MARIA LUISA LOPEZ.VALLEJO, C.A. IGLESIAS, J.C. LOPEZ

FUZZY HYBRID TECHNIQU~ IN MODFI .ING .. . . ~, . . . . . . . . . . . . ; . . . . . . ; . . . . . . . . . . . . . . . . . . . . . . . . . 180 M. DELGADO, ANTONIO F. GOMEZ-SKARMETA, J. GOMEZ MARIN-BLAZQUEZ H. MARTINEZ BARBERA

CHEMICAL PROCESS FAULT DIAGNOSIS USING KERNEL RETROFrITED FUZZY GENETIC ALGORITHM BASED LEARNER (FGAL) WITH A HIDDEN MARKOV

MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 I.BURAK OZYURT, AYDIN K. SUNOL, LAWRENCE O. HALL

ON LINGUISTIC APPROXIMATION WITH GENETIC PROGRAMMING . . . . . . . . . . . . . . . . . . . . . 200 RYSZARD KOWALCZYK

A NEW SOLUTION METHODOLOGY FOR FUZZY RELATION EQUATIONS . . . . . . . . . . . . . . . . 210 SPYROS G. TZAFESTAS, GIORGOS B. STA~WOU

AN APPROACH TO GENERATE MEMBERSHIP FUNCTION BY USING KOHONEN'S

SOFM NETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 MANPING LI, YUY1NG WANG, XIURONG ZHANG

INTEL! JGENT POLICING FUNCTION FOR ATM NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 ANNA RITA CALISTI, FRANCISCO DAVID TRUJILLO AGUILERA, A. D[AZ-ESTRELLA, FRANCISCO SANDOVAL HERNANDEZ

DERIVING FUZZY SUBSETHOOD MEASURES FROM VIOLATIONS OF THE IMPLICATION BETWEEN El . ~ S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 FRANCISCO BOTANA

Uncertainty, Causal Reasoning and Bayesian Networks

OBJEL-q" ORIENTED STOCHASTIC PETRJ NET SIMULATOR: A GENERIC KERNEL FOR HEURISTIC PLANNING TOOLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244 M1QUEL A. PIER.A, ANTONIO J. GAMBIN, RAMON VILANOVA

AN ARTIFICIAL NEURAL NETWORK FOR FI_,ASHOVER PREDICTION.

A PREI JMINARY STUDY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 254 CHRISTIAN W DAWSON, PAUL D WILSON, ALAN N BEARD

FUZZY DECISION MAKING UNDER UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 CENGIZ KAHRAMAN, ETHEM TOLGA

IMPROVING PERFORMANCE OF NAIVE BAYES CLASSIFIER BY INCLUDING HIDDEN VARIABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 B O ZENA STEWART

XIX

Qualitative Reasoning

A SYSTEM HANDLING RCC-8 QUF_~W~ ON 2D REGIONS REPRESENTABLE IN THE CLOSURE ALGEBRA OF HALF-PLANE, S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 BRAtgDON BENNETT, AMAR tSLI, ANTHONY G. COHN

CARDINAL D I ~ I O N S ON EXTENDED OBJECTS FOR QUALITATIVE NA'vqGATtON . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 M. TERESA ESCR1G, FRANCISCO TOLEDO

DEFINITION AND STUDY OF LINEAL EQUATIONS ON ORDER OF MAGNITUDE MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 N(IR1A AGELL, FERNANDO FEBLES, N(]RIA PIERA

A CONSTRAINT-BASED APPROACH TO ASSIGNING SYSTEM COMt~NENTS TO TASKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312 ELISE H. TU~VER, ROY M. TURNER

AUTOMATIC SEMIQUALITATIVE ANALYSIS: APPLICATION TO A BIOMETALLURGICAL SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 RAFAEL MARTINEZ GASCA, JUAN ANTONIO ORTEGA, MIGUEL TORO

INCLUDING QUAI_JTATIVE KNOWI .h-1-)GE IN SEMIQUALITATIVE DYNAMICAL SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 JUAN ANTONIO ORTEGA, RAFAEL MARTINEZ GASCA, M1GUEL TORO

A TOOL TO OBTAIN A HIERARCHICAL QUALITATIVE R U L ~ FROM QUANITI'ATIVE DATA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 JESUS AGUILAR, JOSE R1QUELME, MIGUEC TORO

HYBRIDIZATION TECHNIQUES IN OPTICAL EMISSION SPECTRAL ANALYSIS . . . . . . . . 347 C,S. AMPRATWUM, P.O. PtCTON, A.A. HOPGOOD, a. BROWNE

KADS QUALITATIVE MODEL BASED MOTOR SPE-h-D CONTROL . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 J. RUIZ GOMEZ

NEGLIGIBILITY RELATIONS BETWEEN REAL NUMBERS AND QUAI.JTATIVE LABELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 MONICA S~CHEZ. FRANCESC PRATS, N(IRIA PIERA

QUALITATIVE REASONING UNDER UNC-'t~TAIN KNOWI .E'D, GE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 M. CHACHOUA, D. PACHOLCZYK

QUALITATIVE REASONING FOR ADMISSION CONTROL IN ATM NETWORKS . . . . . . . . . . 387 J.L MARZO, A. BUENO, R. FABREGAT, 7". JOVE

USING TOLERANCE CALCULUS FOR REASONING IN RELATIVE ORDER OF MAGNITUDE MODEI~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 ROBERT DOLLINGER, 10AN ALFRED LETIA

Neural Networks

COMPLEXITY AND COGNITIVE COMPLrrlNG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 0 8 LOURDES MATTOS BRASIL, FERNANDO MENDES DE AZEVEDO, JORGE MUNIZ BARRETO, MONIQUE NOIRHOMME-FRAITURE

Evolutionary Computing

ON DECISION-MAKING IN STRONG HYBRID EVOLUTIONARY ALCa3RITHMS . . . . . . . . . 4 1 8 CARLOS COTTA, JOSI~ M. TROYA

XX

GENERA! ]TED PREDICTIVE CONTROL USING GENETIC ALGORrrHMS (GAGPC). AN APPLICATION TO CONTROL OF A NON-IANEAR PROCESS WITH MODEL UNCERTAINI'Y . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428 XAVIER BLASCO, M1GUEL MART[NEZ, JUAN SENENT, JA VIER SANCHIS

PIPING LAYOUT WIZARD: BASIC CONCEPTS AND ITS POTENTIAL FOR PIPE

ROUTE PLANNING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 438 TERUAKI ITO

INTEGRATION OF CONSTRAINT PROGRAMMING AND EVOLUTION PROGRAMS: APPLICATION TO CHANNEL ROUTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448 ALVARO RUIZ.ANDINO, JOSE J. RUZ

USING A GENETIC.M.CK)RrrHM TO SEI FL-'T PARAMEq'ERS FOR A NEURAL NETWORK THAT PREDICTS AFI_ATOXIN CONTAMINATION IN PEANUTS .. . . . . . . . . . . . . . 460 C.E. HENDERSON, WALTER D. POTTER, R.W. MCCLENDON, G. HOOGENBOOM

INTERACTING WITH ARTICULATED FIGURES WITHIN THE PROVIS PROJECt . . . . . . . 470 HERVF. LUGA, OL1VIER BALET, YVES DUTHEaV, RENF. CAUBET

COMPUTING THE SPANISH MEDIUM El FCTRICAL LINE MAINTENANC~ COST BY MEANS OF EVOLUTION-BASED LEARNING PR(~W.SSES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 OSCAR CORDON, FRANCISCO HERRERA, LUCIANO S.AAVCHEZ

A NEW DISSIMILARITY MEASURE TO hMPROVE THE GA PERFORMANCE .. . . . . . . . . . . . 487 G. RAGHA VENDRA RAO, K. CHIDANANDA GOWDA

Object-Oriented Formulations

STRPLAN: A DISTRIBUTED PLANNER FOR OBJECr-CENTRED APPLICATION DOMAINS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493 RAFAEL BERLANGA LLA VORI

Hybridization Techniques

AN INTEI J JGENT HYBRID SYSTEM FOR KNOWI.EIX3E ACQUISITION . . . . . . . . . . . . . . . . . . . 503 CHIEN-CHANG HSU, CHENG-SEEN HO

USING NEURAL NETS TO LEARN WEIGHTS OF RULES FOR COMPOSITIONAL EXPERT SYSTEMS ..... ; . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 511 PETR BERKA, MAREK SLAMA

CASE-, KNOWl JEFIGE-, AND OPTIMIZATION-BASED HYBRID APPROACH IN AI . . . . . 520 VLADIMIR L DONSKOY

A CONTEXTUAL MODEL OF BELIEFS FOR COMMUNICATING AGENTS . . . . . . . . . . . . . . . . . 528 PIERRE E. BONZON

Context-Sensitive Reasoning

CONTEXT-MEDIATED BEHAVIOR FOR AI APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 538 RO Y M. TURNER

A CONTEXT-SENSITIVE, ITERATIVE APPROACH TO DIAGNOSTIC PROBLEM SOLVING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 546 PINAR OZTORK

XXI

A FRAMEWORK FOR DEVELOPING INTELLIGENT TUTORING SYSTEMS INCORPORATING REUSABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 EMAN EL-SHEIKH, JON STICKLEN

Multi-Agent Systems

THE CLASSIFICATION AND SPEL-TFICATION O F A DOMAIN INDEPENDENT AGENT A R C H I T ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 6 8 A. GOEL, K.S. BARBER

MAVE: A MULTI-AGENT ARCHITECTURE FOR VIRTUAL ENVIRONMENTS . . . . . . . . . . . . . 577 JEFFREY COBLE, KARAN HARBISON

AGENT-BASED SIMULATION OF REACTIVE, PRO-ACTIVE AND SOCIAL ANIMAL

BF~IAV1OUR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 584 CATHOLIJN M. JONKER, JAN TREUR

A FUZZY-NEURAL MULTIAGENT SYSTEM FOR OPTIMISATION OF A ROLL-MII ].

APPLICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596 C.A. IGLESIAS, JOSF. C. GONZ,,i.LEZ, JUAN R. VELASCO

HIGH-LEVEL COMMUNICATION PROTOCOL IN A DISTRIBUTED MULTIAGE?Cr SYSTEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 606 WIDED LEJOUAD-CHAARI, FERIEL MOURIA-BEJI

Divisible Problems

EVOLVING THE SCALE OF GENETIC SEARCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617 JOHN R. PODLENA

ENSEMBLES OF NEURAL N ~ W O R K S FOR ANALOGUE PROBLEMS . . . . . . . . . . . . . . . . . . . . . . 625 DAVID PH1LPOT, TIM HENDTLASS

AN EVOLLrTIONARY ALGORITHM WITH A GENETIC ENCODING SCHEME . . . . . . . . . . . . . . 632 HOWARD COPLAND, TIM HEND TLASS

GENERATING LOOKUP TABLES USING EVOLLrFIONARY ALC~RITHMS . . . . . . . . . . . . . . . . . 640 TL, t4 HENDTLASS

4 Generic Tasks of Analysis

Perception

A GENETIC ALGORITHM FOR IANF_,AR FEATURE EXTRACTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 647 SUCHENDRA M. BHANDARKAR, JOGG ZEPPEN, WALTER O. POTTER

KNOWI.EqX3E REPRESENTATION IN A BLACKBOARD SYSTEM FOR SENSOR DATA INI]ERPRETATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657 S.M.C. PEERS

LDCAL INFORMATION P R ~ S I N G FOR DECISION MAKING IN D ~ R A L I S E D SENSING NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667 SIMUKAI W. UTETE

XXII

A FUZZY LINEAR APPROACH TO RECOGNIZING SIGNAL PROFILES . . . . . . . . . . . . . . . . . . . . . 677 P. FELIX, S. FRAGA, R. MAR[N, S, BARRO

PERFORM~aaXICE OF A SMART VELOCITY SENSOR: THE IMPULSE RETINA . . . . . . . . . . . . . 687 EMMANUEL MAR1LLY, CHISTOPHE COROYER, OLGA CACHARD, ALAIN FAURE

TWO METHODS OF LINEAR CORRELATION SEARCH FOR A KNOWLEDGE BASED

SUPERVISED CLASSIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696 AMEL BORGI, JEAN-MICHEL BAZ1N, HERMAN AKDAG

Natural Language Understanding

TURBIO: A SYSTEMFOR EXTRACTING INFORMATION FROM RESTRICTED- DOMAINTEX S . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 0 8 JORDI TURMO, NEUS CATAI_~, HORACIO RODR[GUEZ

AN APPROACH TO El I .IPSIS DETECTION AND CLASSIFICATION FOR THE

ARABIC LANGUAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 2 KAIS HADDAR, ABDELMAJID BEN HAMADOU

A REVIEW OF EARLY-BASED PARSER FOR TIG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 732 VICTOR JESUS D[AZ, VICENTE CARRILLO, MIGUEL TORO

GENERATING EXPLANATIONS FROM ~ FCI 'RONIC CIRCUITS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739 TAKUSHI TANAKA

System Identification

THE EFFECT OF A DYNAMICAL LAYER IN NEURAL NETWORK PREDICTION OF BIOMASS IN A FERMENTATION PROCESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 749 MAJEED SOUFIAN, MUSTAPHA SOUFIAN, M.J. DEMPSEY

STATE F_ST/MATION FOR NONLINEAR SYSTEMS USING RESTRICTED GENERIC OPTIMIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 758 SANTIAGO GARRIDO, LUIS MORENO, CARLOS BALAGUER

IDENTIFICATION O F A NONLINEAR INDUSTRIAL PROCESS VIA FLr-ZZY

CLUSTERING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 768 BEHZAD MOSHIRI, S.CH. MALEKI

Monitoring

APPLYING COMPUTER VISION TECHNIQUES TO TRAFF/C MONITORING TASKS . . . . . 776 JORGE BADENAS, F1LIBERTO PLA

A SELF-DIAGNOSING DISTRIBUTED MONITORING SYSTEM FOR NUCLEAR PLANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 786 ALDO FRANCO DRAGONI, PAOLO GIORGINI, MAURIZIO PANTI

OVERLOAD SCREENING OF TRANSMISSION SYSTEMS USING NEURAL NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 796 JESUS MANUEL RIQUELME, A. GOMEZ, J.L. MART[NEZ, J.A. PE~AS L~PEZ

×XIII

Faul t D iagnos i s

ON LINE INDUSTRIAL DIAGNOSIS: AN ATTE2vlFf TO APPLY ART/FICIAL INTE! .I JGENCE TECH~, QUES TO P R O S CONTROL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 804 CARLOS ALONSO GONZALEZ, BERLAMINO PULIDO JUNQUERA, GERARDO ACOSTA

AN AI MODEl ].ING APPROACH TO UNDERSTANDING A COMPLt~ I~£A_NUFACFURING PROCESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 814 M.A. RODRIGUES, L, BOTTACI

IDENTIFICATION AND DEFECI" INSPECTION WITH ULTRASONIC TECHNIQUES IN FOUNDRY PIFL-ES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 822 A. LAZARO, 1. SERRANO, J.P. ORIA, C. de MIGUEL

AN OOM-KBES APPROACH FOR FAULT DETECTION AND DIAGNOSIS . . . . . . . . . . . . . . . . . . . 831 YUNFENG XtAO, CILIA It. HAN

MODEL-BASED FAULT SIMULATION: A REDUCTION MEI'HOD FOR THE DIAGNOSIS OF EI,FL--TRICAL COMPONENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 840 A. HEINZELMANN, PAULA CHAMMAS

A MODEL-BASED AUTOMATED DIAGNOSIS ALCdDRITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 848 ALONG LIN

Pred ic t ive Models

CYCIAC FORF~ASTING WITH RECURRENT NEURAL NETWORK . . . . . . . . . . . . . . . . . . . . . . . . . . 857 SHAUN-INN WU

NEW ALGORITHMS TO PREDICI" SECONDARY STRUCTURES OF RNA M A C R O M O L E ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 864 MOURAD ELLOUiVll

A HYBRID GA STATISTICAL METHOD FOR THE F O I S T I N G PROBLEM: THE PREDICTION OFTHE RIVER NILE INFLOWS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 876 ASHRAF H. ABDEL-WAHAB, MOHA.MAfED E. EL-TELBANY, SAMIR L SHAHEEN

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883