The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Gene Expression Programming and the Evolution of Computer Programs
Abstract
In this chapter an artificial problem solver inspired in natural genotype/phenotype systems — gene expression programming — is presented. As an introduction, the fundamental differences between gene expression programming and its predecessors, genetic algorithms and genetic programming, are briefly summarized so that the evolutionary advantages of gene expression programming are better understood. The work proceeds with a detailed description of the architecture of the main players of this new algorithm (chromosomes and expression trees), focusing mainly on the interactions between them and how the simple yet revolutionary structure of the chromosomes allows the efficient, unconstrained exploration of the search space. And finally, the chapter closes with an advanced application in which gene expression programming is used to evolve computer programs for diagnosing breast cancer.
Related Content
P. Chitra, A. Saleem Raja, V. Sivakumar.
© 2024.
24 pages.
|
K. Ezhilarasan, K. Somasundaram, T. Kalaiselvi, Praveenkumar Somasundaram, S. Karthigai Selvi, A. Jeevarekha.
© 2024.
36 pages.
|
Kande Archana, V. Kamakshi Prasad, M. Ashok.
© 2024.
17 pages.
|
Ritesh Kumar Jain, Kamal Kant Hiran.
© 2024.
23 pages.
|
U. Vignesh, R. Elakya.
© 2024.
13 pages.
|
S. Karthigai Selvi, R. Siva Shankar, K. Ezhilarasan.
© 2024.
16 pages.
|
Vemasani Varshini, Maheswari Raja, Sharath Kumar Jagannathan.
© 2024.
20 pages.
|
|
|