Detail of the student project

List
Topic:Fitness Predictors in Genetic Programming
Department:Katedra kybernetiky
Supervisor:Ing. Petr Pošík Ph.D.
Announce as:DP,BP,SOP
Description:Genetic programming is an evolutionary method for searching for algorithms that solve certain problem, or for searching a structured description of certain system, e.g. in the form of a mathematical expression. Evaluation of a candidate solution is usually done with respect to a big set of test cases which is time consuming. That's why the so-called fitness predictors are used. A fitness predictor is a small subset of the set of test cases which is able to provide the evolution with similar information as the whole testing set. The goal of this project is the exploration, design and evaluation of methods for constructing the fitness predictors.
Instruction:1) Learn the principles of GP, fitness predictors and methods for their construction.
2) Design your own method of fitness predictor construction.
3) Compare the known and proposed fitness predictor methods, and evaluate their pros and cons.
Date:10.05.2019
Responsible person: Petr Pošík