Evolutionary Tree Genetic Programming

author = "Jan Antolik",

title = "Evolutionary Tree Genetic Programming",

school = "Department of Computing and Information Sciences, College of Arts and Sciences, Kansan State University",

year = "2004",

type = "Master of Science",

address = "Manhattan, Kansas, USA",

keywords = "genetic algorithms, genetic programming",

URL = "

http://www.ms.mff.cuni.cz/~antoj9am/thesis.pdf",

size = "49 pages",

abstract = "We introduce an extension of a genetic programming (GP) algorithm we call Evolutionary Tree Genetic Programming (ETGP). The biological motivation behind this work is the observation that the natural evolution follows a tree like pattern. We want to simulate similar behaviour in artificial evolutionary systems such as GP. In this thesis we provide multiple reasons why we believe simulation of this phenomenon can be beneficial for GP systems. We present various empirical results from test runs. As the test bed for our experiments two standard benchmark problems for GP systems are used, particularly the Artificial Ant problem and the Multiplexer problem. The performance of the ETGP algorithm is compared to the performance of GP system. Unfortunately no significant speedup is found. Some unexpected behaviors of our system are also identified, and a hypothesis is formulated that addresses the question of why we observe this strange behaviour and the lack of speedup. Suggestions on how to extend the ETGP system to overcome the problems identified by this hypothesis are then presented in the end of our concluding chapter.",

notes = "Approved by: Major Professor William Hsu",