Title: How Evolutionary Algorithms Can Efficiently Explore and Exploit the Search Space

Abstract: Evolutionary Algorithms mimic nature with mechanisms such as selection, crossover and mutation to solve various optimization problems in different fields, including Machine Vision and Information Technology. To properly apply Evolutionary Algorithms, a deep understanding of various selection, crossover and mutation operators is required. However, crucial steps and even more important concepts for any search algorithm are exploration and exploitation. On the other hand, these fundamental concepts are not very well understood among practitioners using evolutionary algorithms. Furthermore, how to measure exploration and exploitation directly is an open problem in the field of Evolutionary Computation. In this talk, I will first introduce the basic ingredients of every evolutionary algorithm and point to many problems and mistakes inexperienced users are facing, as well as different applications of evolutionary algorithms in Machine Vision and Information Technology. In the second part of my talk, our novel direct measure of exploration and exploitation will be explained as based on attraction basins — parts of a search space where each part has its own point called an attractor, to which neighbouring points tend to evolve. Each search point can be associated with a particular attraction basin. If a newly generated search point belongs to the same attraction basin as its parent, the search process is identified as exploitation, otherwise as exploration. In the last part, I will mention some open problems regarding computing attraction basins for continuous problems.

Biography: Marjan Mernik received the MSc and PhD degrees in Computer Science from the University of Maribor in 1994 and 1998, respectively. He is currently a professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science. He was a visiting professor at the University of Alabama at Birmingham, Department of Computer and Information Sciences. His research interests include programming languages, domain-specific (modelling) languages, grammar and semantic inference, and evolutionary computations. He is the Editor-in-Chief of the Journal of Computer Languages, as well as Associate Editors of the Applied Soft Computing Journal, Information Sciences Journal, and Swarm and Evolutionary Computation Journal. He has been named a Highly Cited Researcher for years 2017 and 2018. More information about his work is available at https://lpm.feri.um.si/en/members/mernik/.