neat Genetic Programming: Controlling bloat naturally
نویسندگان
چکیده
منابع مشابه
Quadratic Bloat in Genetic Programming
In earlier work we predicted program size would grow in the limit at a quadratic rate and up to fty generations we measured bloat O(generations ). On two simple benchmarks we test the prediction of bloat O(generations) up to generation 600. In continuous problems the limit of quadratic growth is reached but convergence in the discrete case limits growth in size. Measurements indicate subtree cr...
متن کاملGenetic Programming Bloat without Semantics
To investigate the fundamental causes of bloat, six artificial random binary tree search spaces are presented. Fitness is given by program syntax (the genetic programming genotype). GP populations are evolved on both random problems and problems with “building blocks”. These are compared to problems with explicit ineffective code (introns, junk code, inviable code). Our results suggest the entr...
متن کاملCartesian Genetic Programming: Why No Bloat?
For many years now it has been known that Cartesian Genetic Programming (CGP) does not exhibit program bloat. Two possible explanations have been proposed in the literature: neutral genetic drift and length bias. This paper empirically disproves both of these and thus, reopens the question as to why CGP does not suffer from bloat. It has also been shown for CGP that using a very large number of...
متن کاملMultiobjective Genetic Programming: Reducing Bloat Using SPEA2
This study investigates the use of multiobjective techniques in Genetic Programming (GP) in order to evolve compact programs and to reduce the effects caused by bloating. The proposed approach considers the program size as a second, independent objective besides the program functionality. In combination with a recent multiobjective evolutionary technique, SPEA2, this method outperforms four oth...
متن کاملGenetic Programming Bloat with Dynamic Fitness
Abst rac t . In artificial evolution individuals which perform as their parents are usually rewarded identically to their parents. We note that Nature is more dynamic and there may be a penalty to pay for doing the same thing as your parents. We report two sets of experiments where static fitness functions are firstly augmented by a penalty for unchanged offspring and secondly the static fitnes...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Sciences
سال: 2016
ISSN: 0020-0255
DOI: 10.1016/j.ins.2015.11.010