Abstract. This research examines the cause of code growth (bloat) in genetic programming (GP). Currently there are three hypothesized causes of code growth in GP: protection, drift...
Writing reliable software is difficult. It becomes even more difficult when writing scientific software involving floating-point numbers. Computers provide numbers with limite...
For logic programs with arithmetic predicates, showing termination is not easy, since the usual order for the integers is not well-founded. A new method, easily incorporated in th...
Data structures define how values being computed are stored and accessed within programs. By recognizing what data structures are being used in an application, tools can make app...
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...