The Convergence Mechanism and Strategies for Non-Elitist Genetic Programming

DOI

10.2991/iccsee.2013.640How to use a DOI?

Keywords

non-elitist genetic programming, convergence mechanism, convergence strategy, algorithmic pause time

Abstract

Genetic programming is an evolutionary algorithm that proposed to solve the automatic computer program design problem by J.R.Koza in the 1990s. It has good universality and intelligence, and has been widely applied in the field of computer engineering. But genetic programming is essentially a stochastic optimization algorithm, lack theoretic basis on the convergence of algorithm, which limit the scope of its application in some extent. The convergence mechanism of non-elitist genetic programming was studied in this paper. A recursive estimation of the probability of population contains satisfactory solution with the evolution algebra was established by the analysis of operators’ characteristic parameters, then a sufficient condition of population converge in probability was derived from this estimation, and thereby some operational convergence strategies for many common evolution modes were provided.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - He Ni
AU  - Bo Yu
AU  - Fanming Zeng
AU  - Fengrui Sun
PY  - 2013/03
DA  - 2013/03
TI  - The Convergence Mechanism and Strategies for Non-Elitist Genetic Programming
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 2560
EP  - 2567
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.640
DO  - 10.2991/iccsee.2013.640
ID  - Ni2013/03
ER  -