- author = "Vanio Slavov and Nikolay I. Nikolaev",
- title = "Inductive Genetic Programming and Superposition of Fitness Landscapes",
- booktitle = "Genetic Algorithms: Proceedings of the Seventh International Conference",
- year = "1997",
- editor = "Thomas Back",
- pages = "97--104",
- address = "Michigan State University, East Lansing, MI, USA",
- publisher_address = "San Francisco, CA, USA",
- month = "19-23 " # jul,
- publisher = "Morgan Kaufmann",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "1-55860-487-1",
- broken = "http://www.aubg.bg/faculty/cs/nikolaev/papers/icga97.ps.gz",
-
URL = "
http://citeseer.ist.psu.edu/cache/papers/cs/1016/http:zSzzSzwww.aubg.bgzSzfacultyzSznatscizSznikolaevzSzpaperszSzicga97.pdf/nikolaev97inductive.pdf",
-
URL = "
http://citeseer.ist.psu.edu/nikolaev97inductive.html",
- size = "8 pages",
- abstract = "This paper presents an approach to improving the performance of evolutionary algorithms. The evolutionary search effort is distributed among cooperating subpopulations that correspond to the substructures of the fitness landscape. The idea is to create such subpopulations that flow easily on the simple substructures of the complex fitness landscape structure. We claim that the search on a complex fitness landscape is facilitated if properly integrated with search on its simple components. This evolutionary structured search is applied for solving hard inductive learning tasks. The performance observed while inducing regular grammars from sets of boolean strings demonstrated that the approach mitigates the search difficulties.",
-
notes = "ICGA-97
Except for the reversal of the order of the authors http://citeseer.ist.psu.edu/cache/papers/cs/1016/http:zSzzSzwww.aubg.bgzSzfacultyzSznatscizSznikolaevzSzpaperszSzicga97.pdf/nikolaev97inductive.pdf appears to be almost identical to the published paper.",
