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Author
Quirin Arnaud (European Centre for Soft Computing, Mieres, Hiszpania), Korczak Jerzy (Wrocław University of Economics, Poland)
Title
GramGen : a Genetic Programming System Based on Context Free Grammar
GramGen : system programowania genetycznego oparty na gramatyce bezkontekstowej
Source
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu. Informatyka Ekonomiczna (16), 2010, nr 104, s. 128-147, rys., tab., wyk., bibliogr. 12 poz.
Research Papers of Wrocław University of Economics. Business Informatics
Issue title
Data Mining and Business Intelligence
Keyword
Programowanie genetyczne, Funkcje, Algorytmy genetyczne
Genetic programming, Functions, Genetic algorithms
Note
summ., streszcz.
Abstract
W artykule przedstawiono platformę programowania genetycznego, zwaną GramGen, łączącą ideę algorytmów ewolucyjnych z gramatyką bezkontekstową (CFG). Zadaniem systemu jest generowanie formuł logicznych (drzew genotypowych), które po przekształceniu do drzew fenotypowych (formuł) są w stanie rozwiązać konkretny problem praktyczny. Jako ilustrację podejścia podano przykład wykorzystania GramGen do regresji symbolicznej funkcji CosLog. W artykule opisano szczegółowo główne algorytmy, operatory genetyczne, sposoby definiowania ograniczeń oraz "strojenia" parametrów systemu.(abstrakt oryginalny)

In this paper, a new genetic programming system, called GramGen, is described. The system combines context free grammar (CFG) with genetic programming and uses an extended operator set. The objective of the grammar is to limit the size of the search space by allowing the user to define constraints related to the structure or the simplicity of the discovered formulas. These constraints are taken into account by the use of specific genetic operators. The experiments show that the proposed system allows users not only to discover new knowledge but also improve the performance of existing ones.(original abstract)
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Bibliography
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  1. Back T., Hoffmeister F., Schwefel H. (1991), A survey of evolution strategies, [in:] Proceedings of the 4th International Conference on Genetic Algorithms, Eds. R.K. Belew, L.B. Booker, Morgan Kaufmann, San Diego, pp. 2-9.
  2. Freeman J.J. (1998), A linear representation for GP using context free grammars, [in:] Genetic Programming: Proceedings of the Third Annual Conference, University of Wisconsin, Madison, pp. 72-77.
  3. García-Arnau M, Manrique D., Ríos J., Rodríguez-Patón A. (2007), Initialization method for grammar-guided genetic programming, Knowledge-Based Systems, Vol. 20, No. 2, pp. 127-133.
  4. Goldberg D.E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison--Wesley, Reading, Mass.
  5. Javed R, Bryant B., Crepinsek M., Mernik M., Sprague A. (2004), Context-free grammar induction using genetic programming, [in:] Proceedings of the 42nd Annual ACM Southeast Conference, Eds. S.-M. Yoo, L.H. Etzkorn, ACM, Huntsville, pp. 404-405.
  6. Koza J.R. (1992), Genetic Programming, The MIT Press/Bradford Books, Cambridge.
  7. Manrique D., Márquez R, Rios J., Rodriguez-Paton A (2005), Grammar Based Crossover Operator in Genetic Programming, [in:] Artificial intelligence and knowledge engineering applications: A bio-inspired approach, First International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC 2005), Lecture Notes in Computer Science, Vol. 3562/2005, Las Palmas, pp. 252-261.
  8. Montana D.J. (1994), Strongly typed genetic programming. Technical Report #7866, Bolt Beranek and Newman, Cambridge.
  9. Quirin A. (2005), Discovery of classification rules by an evolutive approach: Application to remote sensing images, PhD Thesis, Louis Pasteur University, Strasbourg [in French].
  10. Ross B.J., Gualtieri A.G., Fueten R, Budkewitsch P. (2002), Hyperspectral image analysis using genetic programming, [in:] Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), New York, pp. 1196-1203.
  11. Schoenauer M., Michałowicz Z. (1997), Evolutionary computation, control and cybernetics, Evolutionary Computation [Special Issue], Vol. 26, No. 3, pp. 307-338.
  12. TIDE (2005). Tidal Inlets Dynamics and Environment, Research Project Supported by the European Commission under the Fifth Framework Programme, contract n° EVK3-CT-2001 -00064, at http://www.istitutoveneto.it/tide.
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ISSN
1899-3192
1507-3858
Language
eng
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