Effects of Population, Generation and Test Case Count on Grammatical Genetic Programming for Integer Lists

This paper investigates how grammatical genetic programming performs for evolving simple integer list manipulation functions. We propose three sub-problems which are related to, or component of integer sorting problem as defined by genetic programming literature. We further investigate the effects of modifying evolutionary parameters, such as the number of generations allowed, number of populations, and number of test cases, on the number and distribution of successful solutions. Finally, we propose an AST based dead-code removal for the intron induced non-functional codes on evolved individuals.