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Tutorial

Mutual Relations of Evolutionary Dynamics, Deterministic Chaos and Complexity

Ivan Zelinka
Department of Computer Science
Faculty of Electrical Engineering and Computer Science VŠB-TUO
Ostrava-Poruba, Czech Republic


Abstract:

This tutorial is focused on mutual intersection of two interesting fields of research i.e. evolutionary algorithms and deterministic chaos. It consists of three parts. The first one will discuss the use of evolutionary algorithms on deterministic chaos control with focusing on simple chaotic systems (logistic, Hennon,…) as well as CML systems exhibiting spatiotemporal chaos. The second part will discuss use of deterministic chaos instead of pseudo-random number generators inside evolutionary algorithms with application on well known evolutionary algorithms (differential evolution, PSO, SOMA, genetic algorithms,..) and test functions. Mutual comparison will be presented, based on our research. Also will be discussed question whether evolutionary dynamics really need pseudo- random numbers or no.

The last, most interdisciplinary part will contain three mutually joined intersections, introducing a novel approach joining evolutionary dynamics, complex networks and CML systems exhibiting chaotic behavior. The first part will discuss a novel method on how dynamics of evolutionary algorithms can be visualized in the form of complex networks. An analogy between individuals in the populations in an arbitrary evolutionary algorithm and the vertices in a complex network will be discussed as well as the relationship between the communications of individuals in a population and the edges in a complex network. The second part will discuss the possibility of how to visualize the dynamics of a complex network by means of coupled map lattices and to control by means of chaos control techniques. The last part will discuss some possibilities on CML systems control, especially by means of evolutionary algorithms. The spirit of this keynote speech is to create a closed loop in the following schematic: evolutionary dynamics --> complex network --> CML system --> control CML --> control evolutionary dynamics. Real-time simulations as well as animations and pictures demonstrating the presented ideas will be presented through this tutorial.

 

Biography:

Ivan Zelinka (born in 1965, ivanzelinka.eu) is currently associated with the Technical University of Ostrava (VSB-TU), Faculty of Electrical Engineering and Computer Science. He graduated consequently at the Technical University in Brno (1995 - MSc.), UTB in Zlin (2001 - Ph.D.) and again at Technical University in Brno (2004 - Assoc. Prof.) and VSB-TU (2010 - Professor).

Prof. Zelinka is responsible supervisor of grant research of Czech grant agency GAČR named a) Highly Scalable Parallel and Distributed Methods of Data Processing in E-science (focused on astroinformatics), b) Softcomputing methods in control, c) Control Algorithm Design by Means of Evolutionary Approach, and co-supervisor of grant FRVŠ - Laboratory of parallel computing. He was also working on numerous grants and two EU projects as member of team (FP5 - RESTORM) and supervisor (FP7 - PROMOEVO) of the Czech team. Prof. Zelinka was awarded by Siemens Award for his Ph.D. thesis, as well as by journal Software news for his book about artificial intelligence. He is a member of the British Computer Society, Machine Intelligence Research Labs (MIR Labs - http://www.mirlabs.org/czech.php), IEEE (committee of Czech section of Computational Intelligence), a few international program committees of various conferences, and three international journals. He is also the founder and editor-in-chief of a new book series entitled Emergence, Complexity and Computation (Springer series 10624, see also www.ecc-book.eu).

 

The length of the tutorial:
two hours.

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