Gene Expression Programming

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Author(s): Baddrud Zaman Laskar (NIT Silchar, India)and Swanirbhar Majumder (NERIST, India)
Copyright: 2017
Pages: 24
Source title: Bio-Inspired Computing for Information Retrieval Applications
Source Author(s)/Editor(s): D.P. Acharjya (School of Computing Science and Engineering, VIT University, India)and Anirban Mitra (Vignan Institute of Technology and Management, India)
DOI: 10.4018/978-1-5225-2375-8.ch010

Keywords: Biologically-Inspired Computing / Information Retrieval / Information Science Reference / Medicine & Healthcare

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Abstract

Gene expression programming (GEP) introduced by Candida Ferreira is a descendant of genetic algorithm (GA) and genetic programming (GP). It takes the advantage of both the optimization and search technique based on genetics and natural selection as GA and its programmatic Darwinian counterpart GP. It is gaining popularity because; it has to some extent eradicated the ‘cons' of both while keeping in the ‘pros'. It is still a new technique not much explored since its introduction in 2001. In this chapter both GA and GP is first discussed followed by the elaborate discussion of GEP. This is followed up by the discussion on research work done is different fields using GEP as a tool followed up by GEP architectures. Finally, here GEP has been used for detection of age from facial features as a soft computing based optimization problem using genetic operators.

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