Download Advances in Artificial Intelligence: 12th Biennial by Andreas Junghanns, Jonathan Schaeffer (auth.), Robert E. PDF

By Andreas Junghanns, Jonathan Schaeffer (auth.), Robert E. Mercer, Eric Neufeld (eds.)

This ebook constitutes the refereed court cases of the twelfth Biennial convention of the Canadian Society for Computational reports of Intelligence, AI'98, held in Vancouver, BC, Canada in June 1998.
The 28 revised complete papers offered including 10 prolonged abstracts have been rigorously reviewed and chosen from a complete of greater than two times as many submissions. The publication is split in topical sections on making plans, constraints, seek and databases; purposes; genetic algorithms; studying and average language; reasoning; uncertainty; and learning.

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Additional resources for Advances in Artificial Intelligence: 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI'98 Vancouver, BC, Canada, June 18–20, 1998 Proceedings

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X| (10) Mereological Theories of Concepts in Granular Computing 5 41 Approximate Reasoning: A Granular Rough Mereological Logic GRML Granulation makes it possible to construct intensional logics, see [2] for this notion, in which possible worlds at which extensions of formulas are evaluated are granules of individuals and states of truth are reals in the interval [0, 1], cf. , [37]. We assume a universal concept U of entities with a part relation π, the corresponding ingredient relation ing, a compatible rough inclusion μ, and a rough inclusion ν on finite concepts (sets); granules g(v, r, μ) are defined as in (3).

Kluwer, Dordrecht (1991) 25. : Rough sets. Int. J. Computer and Information Sci. 11, 341–356 (1982) 26. : Science and Hypothesis, London (1905) 27. : Rough Sets. Mathematical Foundations. Physica Verlag, Heidelberg (2002) 28. : A rough set paradigm for unifying rough set theory and fuzzy set theory (a plenary lecture). , Skowron, A. ) RSFDGrC 2003. LNCS (LNAI), vol. 2639, pp. 70–78. Springer, Heidelberg (2003); cf. Fundamenta Informaticae 54, 67–88 (2003) 29. : Toward rough set foundations. Mereological approach (a plenary lecture).

Clearly: μσt is a rough inclusion; let us observe that μσt (v, 1) is the identity. 5 Granular Topologies Our intuition about granules as neighborhoods of entities can be put into a formal statement. We denote by μt a rough inclusion induced either by an Archimedean t–norm or by a residual implication of a continuous t–norm. uε μt (v, s). (8) We expect that the system {N (v, r) : vεU ; r ∈ [0, 1]} will turn out a neighborhood basis for a topology τμt . This is justified by, Proposition 9. The following hold, 1.

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