Abstract—P systems are computational models that simulate the structure and functions of a living cell. Fuzzy logic deals with approximate reasoning rather than fixed. A classifier system is a machine learning system that helps to create new rules that can be used in classification in order to add new information to a given database. Cell aging is one of the main phases of any cell cycle. The rate of aging progression may vary from a person to another; furthermore, the cells of the same organ do not age in the same rate. In this paper, we are creating a classifier system with the structure and functions of P systems. The proposed classifier P system deals with imprecise biological data of cell aging, so the new rules generated by the system should be evaluated using a fuzzy rule base. Transition rules and inhibitors accompany the P system and executed in a parallel manner.

Index Terms—Classifier systems, fuzzy p systems, natural computing, p systems, p system with inhibitors

The authors are with Faculty of Computers and Information, Cairo University, Egypt. (e-mail: lamia_work@yahoo.com; e-mail: a.badr.fci@gmail.com; e-mail: i.farag@fci-cu.edu.eg).

Cite: Lamiaa Hassaan Ahmed, Amr Ahmed Badr, and Ibrahim Farag Abd El-Rahman, "A Fuzzy Genetic Based Classifier P System to Predict Cell Aging," International Journal of Computer and Electrical Engineering vol. 3, no. 6, pp. 857-864, 2011.