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Knowledge-Driven Computing

Knowledge Engineering and Intelligent Computations

  • Carlos Cotta
  • Simeon Reich
  • Robert Schaefer
  • Antoni Ligęza

Part of the Studies in Computational Intelligence book series (SCI, volume 102)

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Anthony Brabazon, Michael O’Neill
    Pages 17-30
  3. Jolanta Cybulka, Jacek Martinek
    Pages 31-43
  4. Loukas Georgiou, William J. Teahan
    Pages 45-62
  5. Krzysztof Goczyła, Wojciech Waloszek, Teresa Zawadzka, Michał Zawadzki
    Pages 63-80
  6. Alfredo G. Hernández-Díaz, Luis V. Santana-Quintero, Carlos A. Coello Coello, Rafael Caballero, Julián Molina
    Pages 81-98
  7. Beata Jankowska, Magdalena Szymkowiak
    Pages 99-116
  8. Antoni Ligęza, Maroua Bouzid
    Pages 133-148
  9. Adam Meissner, Grażyna Brzykcy
    Pages 149-164
  10. R. Montenegro, G. Montero, E. Rodríguez, J. M. Escobar, J. M. González-Yuste
    Pages 165-182
  11. Josep Lluís de la Rosa, Albert Figueras, Christian Quintero, Josep Antoni Ramon, Salvador Ibarra, Santiago Esteva
    Pages 217-233
  12. Krzysztof Świder, Bartosz Jędrzejec, Marian Wysocki
    Pages 273-288
  13. Wojciech Turek, Robert Marcjan, Krzysztof Cetnarowicz
    Pages 289-303
  14. Francisco Fernández de Vega, Gustavo Olague, Cynthia B. Pérez, Evelyne Lutton
    Pages 305-324

About this book

Introduction

Knowledge-Driven Computing constitutes an emerging area of intensive research located at the intersection of Computational Intelligence and Knowledge Engineering with strong mathematical foundations. It embraces methods and approaches coming from diverse computational paradigms, such as evolutionary computation and nature-inspired algorithms, logic programming and constraint programming, rule-based systems, fuzzy sets and many others. The use of various knowledge representation formalisms and knowledge processing and computing paradigms is oriented towards the efficient resolution of computationally complex and difficult problems.

The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches. More precisely, the ultimate goal has been to collect new knowledge representation, processing and computing paradigms which could be useful to practitioners involved in the area of discussion. To this end, contributions covering both theoretical aspects and practical solutions, and dealing with topics of interest for a wide audience, and/or cross-disciplinary research were preferred.

Keywords

algorithm algorithms computational intelligence description logics evolution fuzzy genetic algorithms intelligence knowledge engineering knowledge representation multi-objective optimization ontology optimization programming simulation

Editors and affiliations

  • Carlos Cotta
    • 1
  • Simeon Reich
    • 2
  • Robert Schaefer
    • 3
  • Antoni Ligęza
    • 4
  1. 1.ETSI Informática (3.2.49) UMAMálagaSpain
  2. 2.Department of MathematicsThe Technion – Israel Institute of TechnologyHaifaIsrael
  3. 3.Institute of InformaticsAGH – University of Science and TechnologyKrakówPoland
  4. 4.Institute of AutomaticsAGH – University of Science and TechnologyKrakówPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77475-4
  • Copyright Information Springer Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-77474-7
  • Online ISBN 978-3-540-77475-4
  • Series Print ISSN 1860-949X
  • Buy this book on publisher's site
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