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Foundations of Intelligent Systems: 12th International by W. Bruce Croft (auth.), Zbigniew W. Raś, Setsuo Ohsuga

By W. Bruce Croft (auth.), Zbigniew W. Raś, Setsuo Ohsuga (eds.)

This e-book constitutes the refereed court cases of the twelfth overseas Symposium on Methodologies for clever platforms, ISMIS 2000, held in Charlotte, NC, united states in October 2000.
The sixty four revised complete papers provided including one invited contribution have been rigorously reviewed and chosen from a complete of 112 submissions. The papers are geared up in topical sections on evolutionary computation, clever details retrieval, clever info platforms, wisdom illustration and integration, wisdom discovery and studying, good judgment for AI, and methodologies.

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Additional resources for Foundations of Intelligent Systems: 12th International Symposium, ISMIS 2000 Charlotte, NC, USA, October 11–14, 2000 Proceedings

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B. and Michalewicz, Z. ) (1997), Handbook of Evolutionary Computation. IOP Publishing Ltd and Oxford: Oxford University Press. M. (1896), A New Factor in Evolution, American Naturalist, vol. 441-51. , San Francisco, CA, 1998. , Panait, L. S. and Brazdil, P. B. ), Guimaraes, Portugal, June 5-7. S. (2000), Experimental Validations of the Learnable Evolution Model, Proceedings of the 2000 Congress on Evolutionary Computation, La Jolla, California. , and Moustafa, R. (1999), Comparing Performance of the Learnable Evolution Model and Genetic Algorithms on Problems in Digital Signal Filter Design.

In this paper, we focus on the actual effects of the phase transition on relational learning, through systematic experiments on artificial problems. We define some hundreds of target concepts, located in the under-constrained, overconstrained and mushy regions. W. Ra´ s and S. ): ISMIS 2000, LNAI 1932, pp. 31–39, 2000. c Springer-Verlag Berlin Heidelberg 2000 32 A. Giordana et al. learning and a test set. The well-known top-down relational learner FOIL [Qui90] is run on these training sets, and the theories learnt by FOIL are compared to the true target concepts.

Attributional calculus stands between propositional calculus and predicate calculus in terms of its representational power. New individuals are generated by a hypothesis instantiation operator that instantiates the given hypothesis in various ways. 3 .. 5 .. S. Michalski where the domains of attributes x, y, and z are: D(x) = {a,b,c,d,e,f}, and D(y) and D(z) range over real numbers between 0 and 10. Rules in (1) characterize two subareas of the search space that contain high performing individuals.

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