Measures of diversity for populations and distances between individuals with highly reorganizable genomes

Evolutionary Computation

Volumn 12, Issue 4, 2004, Pages 495-515

  Mattiussi, Claudio ^a   Waibel, Markus ^a   Floreano, Dario ^a  

^a EPFL   (Switzerland)

Author keywords

Evolutionary computation; Genetic programming; Jaccard similarity; Linguistic complexity; Nucleotide diversity; Population diversity; Substring diversity; Tanimoto distance; Variable length genomes

Indexed keywords

JACCARDO SIMILARITY; LINGUISTIC COMPLEXITY; NUCLEOTIDE DIVERSITY; POPULATION DIVERSITY; SUBSTRING DIVERSITY; TANIMOTO DISTANCE; VARIABLE LENGTH GENOMES;

COMPUTATIONAL COMPLEXITY; EVOLUTIONARY ALGORITHMS; GENES; GENETIC ALGORITHMS; MATHEMATICAL TRANSFORMATIONS; PATTERN RECOGNITION; SET THEORY; TOPOLOGY;

PROBLEM SOLVING;

ARTICLE; BIOLOGICAL MODEL; BIOLOGY; COMPARATIVE STUDY; GENETIC VARIABILITY; GENOME; HUMAN;

COMPUTATIONAL BIOLOGY; GENOME; HUMANS; MODELS, GENETIC; VARIATION (GENETICS);

EID: 10444253956     PISSN: 10636560     EISSN: None     Source Type: Journal    
DOI: 10.1162/1063656043138923     Document Type: Article

References (27)

1. Crochemore, M., Hancart, C., and Lecroq, T. (2001). Algorithmique du texte. Vuibert, Paris.
2. Crochemore, M. and Rytter, W. (2002). Jewels of Stringology. World Scientific, Singapore.
3. de Jong, E., Watson, R., and Pollack, J. (2001). Reducing bloat and promoting diversity using multi-objective methods. In et al., L. S., editor, GECCO 2002, pages 11-18, San Francisco, CA. Morgan Kaufmann.
4. Graur, D. and Li, W.-H. (2000). Fundamentals of Molecular Evolution. Sinauer Associates, Sunderland, MA, 2nd edition.
5. Gusfield, G. (1997). Algorithms on Strings, Trees, and Sequences. Cambridge University Press, Sunderland, MA.
6. Haykin, S. (1999). Neural Networks: A Comprehensive Foundation. Prentice Hall, Upper Saddle River, NY, 2nd edition.
7. Keijzer, M. (1996). Efficiently representing populations in genetic programming. In Angeline, P. et al., editor, Advances in Genetic Programming, volume 2, pages 259-278, CAmbridge, MA. MIT Press.
8. Keller, R. and Banzhaf, W. (1994). Explicit maintenance of genetic diversity on genospaces. Unpublished manuscript. Available online at Citeseer.
9. Langdon, W. and Poli, R. (2002). Foundations of Genetic Programming. Springer, Berlin.
10. Leung, Y., Gao, Y., and Xu, Z. (1997). Degree of population diversity - a perspective on premature convergence in genetic algorithms and its markov chain analysis. IEEE Trans. Neural Networks, 8(5):1165-1176.
11. Levandowsky, M. and Winter, D. (1971). Distance between sets. Nature, 234(5):34-35.
12. Lipkus, A. (1999). A proof of the triangle inequality for the tanimoto distance. J. of Mathematical Chemistry, 26:263-265.
13. Mattiussi, C. and Floreano, D. (2004). Evolution of analog networks using local string alignment on highly reorganizable genomes. In et al., R. Z., editor, Proceedings of the 2004 NASA/DoD Conference on Evolvable Hardware, 24-26 June 2004, Seattle, pages 30-37, Los Alamitos, CA. IEEE Computer Society.
14. McCreight, E. (1976). A space-economical suffix tree construction algorithm. J. ACM, 23(1):262-272.
15. Monro, G. (1987). The concept of multiset. Zeitschr. f. math. Logik ung Grundlagen d. Math., 33:171-178.
16. Morrison, W. and de Jong, K. (2002). Measurement of population diversity. In et al., P. C., editor, EA 2001, volume 2310 of LNCS, pages 31-41, Berlin. Springer.
17. O'Reilly, U.-M. (1997). Using a distance metric on genetic programs to understand genetic operators. In IEEE International Conference on Systems, Man, and Cybernetics, volume 5, pages 4092-4097.
18. Sankoff, D. and Kruskal, J. (1983). Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison. Addison-Wesley, Reading, MA.
19. Shapiro, J. (2002). A 21st century view of evolution. J. Biol. Phys., 28:1-20.
20. Theodoridis, S. and Koutroumbas, K. (2003). Pattern Recognition. Academic Press, Sand Diego, CA, 2nd edition.
21. Tomassini, M., Vanneschi, L., Fernández, F., and Galeano, G. (2004). A study of diversity in multipopulation genetic programming. In et al., P. L., editor, EA 2003, Artificial Evolution: 6th International Conference, Marseilles, France, October 27-30, 2003, volume 2936 of LNCS, pages 243-255, Berlin. Springer.
22. Trifonov, E. (1990). Making sense of the human genome. In Sarma, R. and Sarma, M., editors, Structure and Methods, volume 1, pages 69-77. Adenine Press, New York.
23. Troyanskaya, O., Arbell, O.and Koren, Y., Landau, G., and Bolshoy, A. (2002). Sequence complexity of prokariotic genomic sequences: A fast algorithm for calculating linguistic complexity. Bioinformatics, 18(5):679-688.
24. Ukkonen, E. (1995). On-line construction of suffix trees. Algorithmica, 14:249-260.
25. Wineberg, M. and Oppacher, F. (2000). Enhancing the ga's ability to cope with dynamic environments. In et al., D. W., editor, GECCO 2000, pages 3-10, San Francisco, CA. Morgan Kaufmann.
26. Wineberg, M. and Oppacher, F. (2003a). Distance between populations. In et al., E. C.-P., editor, GECCO 2003, volume 2724 of LNCS, pages 1481-1492, Berlin. Springer.
27. Wineberg, M. and Oppacher, F. (2003b). The underlying similarity of diversity measures used in evolutionary computation. In et al., E. C.-P., editor, GECCO 2003, volume 2724 of LNCS, pages 1493-1504, Berlin. Springer.