Visualization of a Simple Genetic Algorithm for Pedagogical

Visualization of a Simple Genetic Algorithm for Pedagogical Purposes Vedrana Vidulin Bogdan Filipič Jožef Stefan Institute, Department of Intelligent Systems vedrana. vidulin@ijs. si bogdan. filipic@ijs. si

• Motivation: – To facilitate the explanation of how genetic algorithms work. • SGA Algorithm: – Based on the Simple Genetic Algorithm described in [Goldberg, 1989].

Problem Solved by SGA (1) 364 22 + 23 + 25 + 26 + 28 0 1 1 0 0

Problem Solved by SGA (2) • Fitness function • Coefficient • Generation consisted of 10 solutions • Roulette-wheel selection

Forms of Graphical Representation Colored Strings Statistics Graphical Representation of Best-so-far Fitness

Program Functions Actions Inputs

Recommended GA Sources • A. E. Eiben, J. E. Smith, Introduction to Evolutionary Computing, Springer, 2003 • Genetic Algorithm – Wikipedia, 2006, http: //en. wikipedia. org/wiki/Genetic_algorithm • D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989 • R. L. Haupt, S. E. Haupt, Practical Genetic Algorithms, 2 nd Edition, Wiley-Interscience, 2004 • M. Obitko, P. Slavik, Visualization of genetic algorithms in a learning environment, Spring Conference on Computer Graphics SCCG'99, Comenius University, Bratislava, p. 101 -106, 1999 • R. E. Smith, D. E. Goldberg, J. A. Earickson, SGA-C: A C-language Implementation of a Simple Genetic Algorithm, The Clearinghouse for Genetic Algorithms, Technical Report No. 91002, University of Alabama, Department of Engineering Mechanics, Tuscaloosa 1994