Does data-model co-evolution improve generalization performance of evolving learners?

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1498 LNCS, Issue , 1998, Pages 540-549

  Shapiro, J L ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

CO-EVOLUTION; DATA SET; FINITE POPULATION; GENERALIZATION PERFORMANCE; LARGE POPULATION; LEARNING PARAMETERS;

POPULATION STATISTICS;

EID: 2542590449     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0056896     Document Type: Conference Paper

References (6)

1. Hillis, W.D. Co-evolving Parasites Improve Simulated Evolution as an Optimization Procedure, Physica D 42, 228-234 (1990).
2. Paredis, Jan, Coevolutionary Algorithms from the Handbook of Evolutionary Computation, Back, T. Fogel, D. Michalewicz Z. (eds.) Oxford University Press, 1997.
3. Paredis, Jan, Coevolving Cellular Automata: Beware of the Red Queen!, Proceedings of the Seventh Conference on Genetic Algorithms, Back, T. editor, 393-399, 1997.
4. Rattray, M Modelling the Dynamics of Genetic Algorithms Using Statistical Mechanics, University of Manchester Ph.D. thesis, 1996.
5. Rosin, CD., Coevolutionary Search Among Adversaries, University of California Ph.D. thesis, 1997.
6. Valiant, L.G. A theory of the learnable, Communications of the ACM, 27 no. 11, 1134-1142, 1984.