Modularity in Genetic Programming

author = "Martin Dostal",

title = "Modularity in Genetic Programming",

booktitle = "Handbook of Optimization",

publisher = "Springer",

year = "2013",

editor = "Ivan Zelinka and Vaclav Snasel and Ajith Abraham",

volume = "38",

series = "Intelligent Systems Reference Library",

chapter = "15",

pages = "365--393",

keywords = "genetic algorithms, genetic programming",

isbn13 = "978-3-642-30503-0",

URL = "

http://dx.doi.org/10.1007/978-3-642-30504-7_15",

DOI = "

doi:10.1007/978-3-642-30504-7_15",

abstract = "This chapter provides a review of methods for automatic modularisation of programs evolved using genetic programming. We discuss several techniques used to establishing modularity in program evolution, including highly randomised techniques, techniques with beforehand specified structure of modules, techniques with evolvable structure and techniques with heuristic identification of modules. At first, simple techniques such as Encapsulation and Module Acquisition are discussed. The next two parts reviews Automatically Defined Functions and Automatically Defined Functions with Architecture Altering Operations that enable to evolve the structure of modules at the same time of evolving the modules itself. The following section is focused on Adaptive Representation through Learning, a technique with heuristic-based identification of modules. Next, Hierarchical Genetic Programming is described. Finally, establishing recursion and iteration, a code reuse technique closely related to modularization, is briefly surveyed.",

notes = "University Olomouc, Czech Republic",