Paper Info
Title
Automated problem decomposition for the boolean domain with genetic programming
Abstract
Researchers have been interested in exploring the regularities and modularity of the problem space in genetic programming (GP) with the aim of decomposing the original problem into several smaller subproblems. The main motivation is to allow GP to deal with more complex problems. Most previous works on modularity in GP emphasise the structure of modules used to encapsulate code and/or promote code reuse, instead of in the decomposition of the original problem. In this paper we propose a problem decomposition strategy that allows the use of a GP search to find solutions for subproblems and combine the individual solutions into the complete solution to the problem.
Year
DOI
Venue
2013
10.1007/978-3-642-37207-0_15
EuroGP
Keywords
Field
DocType
automated problem decomposition,gp emphasise,problem space,boolean domain,genetic programming,original problem,smaller subproblems,problem decomposition strategy,complete solution,code reuse,gp search,complex problem
Overlapping subproblems,Computer science,Genetic programming,Theoretical computer science,Cartesian genetic programming,Artificial intelligence,Boolean domain,Problem space,Complex problems,Mathematical optimization,Code reuse,Modularity,Machine learning
Conference
Citations 
PageRank 
References 
6
0.50
12
Authors
2
Name
Order
Citations
PageRank
Fernando E. B. Otero130621.29
Colin G. Johnson2933115.57