- author = "Xin Li and Chi Zhou and Weimin Xiao and Peter C. Nelson",
- title = "Direct Evolution of Hierarchical Solutions with Self-Emergent Substructures",
- booktitle = "The Fourth International Conference on Machine Learning and Applications (ICMLA'05)",
- year = "2005",
- pages = "337--342",
- address = "Los Angeles, California",
- month = dec # " 15-17",
- publisher = "IEEE press",
- keywords = "genetic algorithms, genetic programming, Prefix Gene Expression Programming",
-
URL = "
http://www.cs.uic.edu/~xli1/papers/Substructures(ICMLA05)_XLi.pdf",
- abstract = "Linear genotype representation and modularity have continuously received extensive attention from the Genetic Programming (GP) community. The advantages of a linear genotype include a convenient and efficient implementation scheme. However, most existing techniques using a linear genotype follow the imperative programming language paradigm and a direct hierarchical composition for the functionality of the solution is under achieved. Our work is based on Prefix Gene Expression Programming (P-GEP), a new GP method featured by a prefix notation based linear genotype representation. Since P-GEP uses a functional language paradigm, its framework results in natural self emergence of substructures as functional components during the evolution. We propose to preserve and use potentially useful emergent substructures via a dynamic substructure library, empowering the algorithm to focus the search on a higher level of the solution structure. Preliminary experiments on the benchmark regression problems have shown the effectiveness of this approach.",
-
notes = "cited by \cite{Spector:2011:GECCO}
http://www.cs.csubak.edu/~icmla/icmla05/CFP_Program.html
",
