This article introduces our new approach to program representation for genetic programming (GP). We replace the usual s-expression representation scheme by a strongly-typed ion-ba...
This paper proposes two new methods for optimizing objectives and constraints. The GP approach is very general and hardware resources in finite wordlength implementation of it allo...
Inspired by genetic programming (GP), we study iterative algorithms for non-computable tasks and compare them to naive models. This framework justifies many practical standard tri...
This paper describes POPE-GP, a system that makes use of the NSGA-II multiobjective evolutionary algorithm as an alternative, parameter-free technique for eliminating program bloat...
Yaniv Bernstein, Xiaodong Li, Victor Ciesielski, A...
One crucial issue in genetic programming (GP) is how to acquire promising building blocks efficiently. In this paper, we propose a GP method (called GPTM, GP with Tree Mining) whi...