Function Set Structure Influence onto GPA Efficiency

Tomas Brandejsky

doi:10.13164/mendel.2017.1.029

Tomas Brandejsky

DOI: https://doi.org/10.13164/mendel.2017.1.029

Keywords: Genetic Programming Algorithm, Efficiency, Function set, Function set structure, Inapplicable functions, mutually replaceable functions

Abstract

The paper discusses the influence of function set structure onto efficiency of GPA (Genetic Programming Algorithms), and hierarchical algorithms like GPA-ES (GPA with Evolutionary Strategy to separate parameter optimization) algorithm efficiency. On the foreword, the discussed GPA algorithm is described. Then there is depicted function set and common requirements to its structure. On the end of this contribution, the test examples and environment as well as results of measurement of influence of superfluous functions presence in the used function set is discussed.

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