Multi-layered evolutionary system suitable to symbolic model regression

Presented paper deals with description of multilayered evolutionary system optimized to symbolic regression of difficult systems like e.g. deterministic chaos ones. This paper starts with brief introduction of previous work and ideas. Then the structure of Genetic Programming Algorithm - Evolutionary Strategy hybrid system is described and analyzed including such problems as suitability to parallel implementation, optimal set of building blocks, or initial population generating rules. GPA-ES system combines GPA to model development with ES used for model parameter identification. Such hybrid system eliminates many weaknesses of standard GPA. The paper ends with examples of GPAES application.