Tutorial List
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A Gentle Introduction to Evolutionary Computation by Xin Yao
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Metaheuristics for Multiobjective Optimization by Carlos A. Coello Coello
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Tutorial on Cultural Algorithms by Robert G. Reynolds
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Introduction to Particle Swarm Optimization by James Kennedy and Russell C. Eberhart
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Tutorial on Cultural Algorithms
DESCRIPTION:
Cultural Algorithms are computational models of Cultural Evolution. They consist of two basic components, a population space, and a belief space. The two components interact by means of a Vote-Inherit-Promote or VIP protocol. A variety of paradigms have been used to model the population component including Genetic Algorithms, Genetic Programming, Evolution Strategies, and Evolutionary Programming, Cellular Automata, and Multi-agent systems among others. Likewise the knowledge acquired by the problem solving activities of the population can be stored in the belief space in the form of production rules, semantic networks, version spaces, among others.
As such, Cultural Algorithms represent a general framework for producing hybrid evolutionary systems that integrate evolutionary search and symbolic reasoning together. Cultural Algorithms are particularly useful for problems whose solution requires extensive domain knowledge. The tutorial starts by providing a brief motivation for the Cultural Algorithm framework. Next the basic choices for configuring Cultural Algorithms are presented and the motivation for selected particular configurations will be discussed. The tutorial will conclude with example applications from a variety of application areas including function optimization, knowledge based system design and maintenance, software engineering, and the modeling of complex social systems.
SPEAKER'S INFO:Dr. Robert G. Reynolds received his M.S. and Ph.D. in Computer Science from the University of Michigan-Ann Arbor in 1978 and 1979 respectively in Artificial Intelligence specializing in Genetic Algorithms. He is currently a Professor of Computer Science at Wayne State University and an Adjunct Research Associate at the University of Michigan Ann Arbor. Dr. Reynolds is particularly interested in evolutionary models of Cultural Systems. He developed Cultural Algorithms as a computational framework in which to model cultural evolution. His research has been supported by grants from both NSF and industry. Dr. Reynolds has co-authored two books, and written over 100 articles in the area of evolutionary computation. He is currently an Associate Editor of IEEE Transactions on Evolutionary Computation, International Journal on Tools for Artificial Intelligence, and the International Journal of Software Engineering and Knowledge Engineering. He has been active in the Evolutionary Programming Society and served in various conference committees including Co-Chair of the technical program for Evolutionary Programming in 1995, and 1997.
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Metaheuristics for Multiobjective Optimization
DESCRIPTION:
This tutorial provides with a general picture of the current state-of-the-art in multiobjective optimization using metaheuristics. First, some historical background is provided, dating back to the origins of multiobjective optimization in general. This discussion motivates the use of metaheuristics for solving multiobjective problems and includes a brief description of some of the first approaches proposed in the literature. Then, a discussion on different heuristics used for multiobjective optimization is provided. This discussion includes evolutionary algorithms, simulated annealing, tabu search, scatter search, the ant system, distributed reinforcement learning, particle swarm optimization, artificial immune systems and cultural algorithms. A brief analysis of the literature is also provided. The tutorial finishes with a discussion of some of the research topics that seem more promising for the next few years.SPEAKER'S INFO:
Dr. Carlos A. Coello Coello
CINVESTAV-IPN
Seccion de Computacion
Depto. de Ingenieria Electrica
Av. IPN # 2508
Col. San Pedro Zacatenco
Mexico, D.F. 07300
MEXICO
Phone: +52 55 5747 3800 x 6564
Fax: +52 55 5747 7002
email: ccoello@cs.cinvestav.mx
SHORT BIOGRAPHICAL INFO:
Carlos Artemio Coello Coello received a BSc in Civil Engineering from the Universidad Autónoma de Chiapas in Mexico in 1991. Then, he was awarded a scholarship from the Mexican government to pursue graduate studies in Computer Science at Tulane University. He received a MSc and a PhD in Computer Science in 1993 and 1996, respectively. His PhD thesis was one of the first in the field now called evolutionary multiobjective optimization. Dr. Coello has been a Senior Research Fellow in the Plymouth Engineering Design Centre (in England) and a Visiting Professor at DePauw University (in the USA). He is currently associate professor at CINVESTAV-IPN in Mexico City, Mexico.
He has published over 80 papers in international peer-reviewed journals and conferences and one book on evolutionary multiobjective optimization which is part of the Genetic Algorithms and Evolutionary Computation Series edited by David E. Goldberg. He has also served as a technical reviewer for a number of journals and international conferences and actually serves as associate editor of the IEEE Transactions on Evolutionary Computation.
His current research interests are: evolutionary multiobjective optimization, constraint-handling techniques for evolutionary algorithms and evolvable hardware.
DESCRIPTION
Evolution has created wonders like ourselves. There is much to be learned from Nature. Evolutionary computation is the study of computational systems which use ideas and get inspirations from natural evolution.
This talk introduces the basic ideas and concepts behind evolutionary computation. The relationship between various evolutionary computation techniques and some well-known techniques in artificial intelligence and computer science will be discussed. The establishment of such relationships help to put evolutionary computation in a larger picture and help to better understand when, how and why evolutionary computation techniques work.SPEAKER'S INFO:
Refer to my homepage at here