Modern genetic algorithms

speaker:
Prabhas Chongstitvatana
Department of Computer Engineering
Chulalongkorn University

Abstract

Genetic algorithms are an approach to computation that emphasize on a general purpose search algorithm that uses principles inspired by population genetics to evolve solutions to the problems. GA has become increasingly popular in recent year as a method for solving complex search problems in a large number of disciplines.

I view GA as the process of 'innovation' where the 'building blocks' are integrated into a design. A lot of progress has been made in the last five years. Many new developments such as probabilistic model building genetic algorithms, linkage learning and many others. I will report on these areas and summarise the current development of the theory of evolutionary computation.

Biography

Prabhas Chongstitvatana earned his first degree in electrical engineering from Kasetsart university in 1979. He was awarded PhD from the department of artificial intelligence, Edinburgh university in 1992. His current research focusses on evolutionary computation where he applied genetic search method to robot learning tasks and logic synthesis. He is interested in inter-disciplinary research such as bioinformatics and applying EC to other disciplines; mechanical design, structural design, biological modelling etc.