Evolving Compact Solutions in Genetic Programming: A Case Study

. Genetic programming (GP) is a variant of genetic algorithmswhere the data structures handled are trees. This makes GP especiallyuseful for evolving functional relationships or computer programs, asboth can be represented as trees. Symbolic regression is the determinationof a function dependence y = g(x) that approximates a set of datapoints (x i ; y i ). In this paper the feasibility of symbolic regression withGP is demonstrated on two examples taken from different domains. Furthermore...