Numeric Mutation: Improved Search in Genetic Programming

Genetic programming is relatively poor at discovering useful numeric constants for the terminal nodes of its sexpression trees. In this paper we outline an adaptation to genetic programming, called numeric mutation. ~,Ve provide empirical evidence and analysis that demonstrate that numeric mutation makes a statistically significant increase in genetic programming’s performance for symbolic regression problems.