Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Conference paper
Title: The max problem revisited: the importance of mutation in genetic programming
Author: Kotzing, T.
Sutton, A.
Neumann, F.
O'Reilly, U.
Citation: Proceedings of the 14th International Conference on Genetic and Evolutionary Computation, held in Philadelphia, Pennsylvania, 7-11 July, 2012 / T. Soule (ed.): pp.1333-1340
Publisher: Association for Computing Machinery
Publisher Place: online
Issue Date: 2012
ISBN: 9781450311779
Conference Name: Genetic and Evolutionary Computation Conference (14th : 2012 : Philadelphia, Pennsylvania)
Editor: Soule, T.
Statement of
Timo Kötzing, Andrew M. Sutton, Frank Neumann and Una-May O'Reilly
Abstract: This paper contributes to the rigorous understanding of genetic programming algorithms by providing runtime complexity analyses of the well-studied Max problem. Several experimental studies have indicated that it is hard to solve the Max problem with crossover-based algorithms. Our analyses show that different variants of the Max problem can provably be solved using simple mutation-based genetic programming algorithms. Our results advance the body of computational complexity analyses of genetic programming, indicate the importance of mutation in genetic programming, and reveal new insights into the behavior of mutation-based genetic programming algorithms.
Keywords: Genetic programming
runtime analysis
Rights: Copyright 2012 ACM
DOI: 10.1145/2330163.2330348
Published version:
Appears in Collections:Aurora harvest 4
Computer Science publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.