Intelligent Problem Solving. Methodologies and Approaches

13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000 New Orleans, Louisiana, USA, June 19–22, 2000 Proceedings

  • Rasiah Logananthara
  • Günther Palm
  • Moonis Ali
Conference proceedings IEA/AIE 2000
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1821)

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Keynote Presentation

    1. Pramod K. Varshney
      Pages 1-3
  3. Intelligent Agents I

    1. Christos Stergiou, Jeremy Pitt, Frank Guerin, Alexander Artikis
      Pages 4-13
    2. A. Felfernig, G. Friedrich, D. Jannach, M. Zanker
      Pages 24-33
  4. Artificial Neural Network I

    1. Simon Feraday, Chris Harris, Kihong Shin, Mike Brennan, Malcolm Lindsay
      Pages 46-55
    2. J. A. Steele, L. A. Martin, A. Moyes, S. D. J. McArthur, J. R. McDonald, D. Young et al.
      Pages 56-67
  5. Data Mining I

    1. Miguel A. Serrano, Doris L. Carver, Carlos Montes de Oca
      Pages 79-84
    2. Bruce Wooley, Susan Bridges, Julia Hodges, Anthony Skjellum
      Pages 85-92
    3. Gibbons W M, Ranta M, Scott T M, Mantyla M
      Pages 93-98
  6. Combinatorial Optimization

  7. Expert Systems I

    1. Arne Bultman, Joris Kuipers, Frank van Harmelen
      Pages 139-149
    2. Chunsheng Yang, Kuniji Kose, Sieu Phan, Pikuei Kuo
      Pages 149-160
    3. J. Menal, A. Moyes, S. McArthur, J. A. Steele, J. McDonald
      Pages 160-167

About these proceedings

Introduction

The focus of the papers presented in these proceedings is on employing various methodologies and approaches for solving real-life problems. Although the mechanisms that the human brain employs to solve problems are not yet completely known, we do have good insight into the functional processing performed by the human mind. On the basis of the understanding of these natural processes, scientists in the field of applied intelligence have developed multiple types of artificial processes, and have employed them successfully in solving real-life problems. The types of approaches used to solve problems are dependant on both the nature of the problem and the expected outcome. While knowledge-based systems are useful for solving problems in well-understood domains with relatively stable environments, the approach may fail when the domain knowledge is either not very well understood or changing rapidly. The techniques of data discovery through data mining will help to alleviate some problems faced by knowledge-based approaches to solving problems in such domains. Research and development in the area of artificial intelligence are influenced by opportunity, needs, and the availability of resources. The rapid advancement of Internet technology and the trend of increasing bandwidths provide an opportunity and a need for intelligent information processing, thus creating an excellent opportunity for agent-based computations and learning. Over 40% of the papers appearing in the conference proceedings focus on the area of machine learning and intelligent agents - clear evidence of growing interest in this area.

Keywords

AI applications Artificial intelligence evolutionary algorithm expert system expert systems information system information systems intelligence knowledge discovery modeling neural computation neural network optimization pattern recognition proving

Editors and affiliations

  • Rasiah Logananthara
    • 1
  • Günther Palm
    • 2
  • Moonis Ali
    • 3
  1. 1.The Center for Advanced Computer StudiesUniversity of LousianaLafayetteUSA
  2. 2.Department of Neural Information ProcessingUniversity of UlmUlmGermany
  3. 3.Department of Computer ScienceSouthwest Texas State UniversitySan MarcosUSA

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-45049-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2000
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-67689-8
  • Online ISBN 978-3-540-45049-8
  • Series Print ISSN 0302-9743