This course offers basic knowledge about the class of evolutionary methods used in solving computer science problems. This includes genetic algorithms, evolutionary strategies, genetic programming, problem representations, genetic operations, theory of evolutionary algorithms. Various approaches and applications of evolutionary computation to combinatorial optimization problems are introduced.
Evolutionary computation provides approximate solutions to various scientific and engineering problems in polynomial time. Class of such problems include continuous and combinatorial optimization problems, optimum parameter sets for machine learning, adaptive systems, automated design. This course offers in depth
knowlegde about which evolutionary methods exists, which problems they can be applied, and how successful they are. Students will implement some of these algorithms and present latest achievements in the field.