Fitness Landscapes and Inductive Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Slavov:1997:fliGP,

• author = "Vanyo Slavov and Nikolay I. Nikolaev",
• title = "Fitness Landscapes and Inductive Genetic Programming",
• booktitle = "Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference, ICANNGA97",
• year = "1997",
• editor = "George D. Smith and Nigel C. Steele and Rudolf F. Albrecht",
• pages = "414--418",
• address = "University of East Anglia, Norwich, UK",
• publisher = "Springer-Verlag",
• note = "published in 1998",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-211-83087-1",
• broken = "http://www.aubg.bg/faculty/cs/nikolaev/papers/icannga97.ps.gz",
• URL = "http://citeseer.ist.psu.edu/cache/papers/cs/1016/http:zSzzSzwww.aubg.bgzSzfacultyzSznatscizSznikolaevzSzpaperszSzicannga97.pdf/fitness-landscapes-and-inductive.pdf",
• URL = "http://citeseer.ist.psu.edu/nikolaev97inductive.html",
• DOI = "doi:10.1007/978-3-7091-6492-1_91",
• abstract = "This paper proposes a study of the performance of inductive genetic programming with decision trees. The investigation concerns the influence of the fitness function, the genetic mutation operator and the categorical distribution of the examples in inductive tasks on the search process. The approach uses statistical correlations in order to clarify two aspects: the global and the local search characteristics of the structure of the fitness landscape. The work is motivated by the fact that the structure of the fitness landscape is the only information which helps to navigate in the search space of the inductive task. It was found that the analysis of the landscape structure allows tuning the landscape and increasing the exploratory power of the operator on this landscape.",
• notes = "broken Aug 2020 http://www.sys.uea.ac.uk/Research/ResGroups/MAG/ICANNGA97/papers_frame.html

  GPDT investigates fitness landscape using mutation as genetic operator and calculates fitness distance correlation, fitness autocorrelation and fitness correlation length for random walks. This analysis prompts improved choices for system components such as mutation rate.",

}

Genetic Programming entries for Vanio Slavov Nikolay Nikolaev

Citations