460-4086 – Biologically Inspired Algorithms (BIA)

The aim of the course is to acquaint its students with modern computational methods derived from evolutionary and biological processes (evolutionary algorithms, cellular automata, etc.). The graduate will learn to program and use popular algorithms in the field of evolution and swarm intelligence and apply them to real problems. He will also gain an overview of modern computational procedures based on principles observed from biological processes and dynamics. Upon successful completion of the course, the graduate will be able to apply the methods discussed in the course to real problems of practice.

The course will discuss a wider range of evolutionary computing techniques. Both historically classical techniques and modern algorithms will be mentioned. Evolutionary algorithms and swarm intelligence such as simulated annealing, genetic algorithm, differential evolution, particle swarm, SOMA and others will be discussed. In the second part, the student gets acquainted with symbolic regression and its use in the synthesis of algorithms, classifiers or control programs. After completing the course, the student should have comprehensive knowledge of the above areas, including the possibility of their use. Part of the course is laboratory exercises, in which students will practice both programmings of selected algorithms and their application to solving practical problems.

1. Back, T., Fogel, B., Michalewicz, Z.: Handbook of Evolutionary Computation, Institute of Physics, London 2. Davis L. 1996, Handbook of Genetic Algorithms, International Thomson Computer Press, ISBN 1850328250 3. Koza J.R. 1998, Genetic Programming, MIT Press, ISBN 0-262-11189-6 4. Price,K.,Storn,R.,etal.:DifferentialEvolution-APracticalApproachtoGlobalOptimization. Springer, Heidelberg

5. Ilachinsky A., Cellular Automata: A Discrete Universe, World Scientific Publishing, ISBN 978-9812381835, 2001 6. Hilborn R.C.1994, Chaos and Nonlinear Dynamics, Oxford University Press, ISBN 0-19-508816-8, 1994 7. Gheorghe Paun (Author), Grzegorz Rozenberg (Author), Arto Salomaa, DNA Computing: New Computing Paradigms, Springer, ISBN 978-3540641964