Artificial Intelligence for Advanced Problem Solving Techniques

Artificial Intelligence for Advanced Problem Solving Techniques

Indexed In: SCOPUS
Release Date: January, 2008|Copyright: © 2008 |Pages: 388
DOI: 10.4018/978-1-59904-705-8
ISBN13: 9781599047058|ISBN10: 1599047055|EISBN13: 9781599047072
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Description & Coverage
Description:

One of the most important functions of artificial intelligence, automated problem solving, consists mainly of the development of software systems designed to find solutions to problems. These systems utilize a search space and algorithms in order to reach a solution.

Artificial Intelligence for Advanced Problem Solving Techniques offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning, and highlights the relationship between the search categories and the various ways a specific application can be modeled and solved using advanced problem solving techniques.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Neural Networks
  • Automated Planning
  • CaRBS Systematic Search Algorithms
  • Constraint Satisfaction and Scheduling
  • Distributed Online Planning
  • Fuzzy Optimization
  • Genetic Algorithms and Programming
  • Language Evolution
  • Machine Learning
  • Optimal and Suboptimal Temporal Planning
  • Optimising Object Classification
  • Parallelizing Genetic Algorithms
  • Principles of Constraint Processing
  • PROMETHEE
  • Recursive Unsupervised Learning
  • Reinforcement Learning
  • Stratified Constraint Satisfaction Networks
  • Synergetic Multi-Agent Simulations
  • Trigonometric Differential Evolution
  • Uncertain Reasoning-Based Analysis
Reviews & Statements

This book aims to provide the user with knowledge about the principles of Artificial Intelligence and about innovative methodologies that utilize the effort spent by researchers in various different fields in order to build effective problem-solving systems.

– Dimitris Vrakas, Aristotle University, Greece

This collection offers scholars and practitioners cutting-edge research on algorithms and techniques such as search, domain independent heuristics, scheduling, constraint satisfaction, optimization, configuration, and planning.

– APADE (2008)

This book has been written to teach IT researchers, system engineers and students about the latest research on automated problem solving.

– Book News Inc. (June 2008)

The book is suitable for postgraduates, researchers and practitioners in planning, scheduling, optimization, machine learning, and advanced problem solving. The book is a valuable addition to any science library.

– H. Yousef, INVISTA Performance Technologies, Journal of the Operational Research Society (2010)
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Editor/Author Biographies
Dr. Ioannis Vlahavas is a professor at the Department of Informatics at the Aristotle University of Thessaloniki. He received his Ph.D. degree in Logic Programming Systems from the same University in 1988. During the first half of 1997 he was a visiting scholar at the Department of CS at Purdue University. He specializes in logic programming, knowledge based and AI systems and he has published over 100 papers, 9 book chapters and co-authored 4 books in these areas. He teaches logic programming, AI, expert systems, and DSS. He has been involved in more than 15 research projects, leading most of them. He was the chairman of the 2nd Hellenic Conference on AI and the local organizer of the 2nd International Summer School on AI Planning. He is leading the Logic Programming and Intelligent Systems Group (LPIS Group, lpis.csd.auth.gr) (more information at www.csd.auth.gr/~vlahavas)
Dimitris Vrakas is finishing his PhD in Distributed Planning and Scheduling at the Dept of Informatics of the Aristotle University of Thessaloniki. His interests also include Machine Learning, Problem Solving and Heuristic Search Algorithms. He has published several articles and presented various papers on important aspects of Automated Planning such as Learning aided Planning Systems. He has taken part in several projects such as PacoPlan, a web–based system combining Planning and Constraint Programming. He is a member of the American Association for Artificial Intelligence, the Association of Greek Informaticians and the Hellenic Society for Artificial Intelligence.
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