Download Current Topics in Artificial Intelligence: 11th Conference by Roque Marín, Eva Onaindía, Alberto Bugarín, José Santos PDF

By Roque Marín, Eva Onaindía, Alberto Bugarín, José Santos

This ebook constitutes the completely referred post-proceedings of the eleventh convention of the Spanish organization for man made Intelligence, CAEPIA 2005, held in Santiago de Compostela, Spain in November 2005.

The forty eight revised complete papers provided including an invited paper have been conscientiously chosen in the course of rounds of reviewing and development from an preliminary overall of 147 submissions. The papers span the complete spectrum of man-made intelligence from foundational and theoretical concerns to complicated functions in a number of fields.

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Extra resources for Current Topics in Artificial Intelligence: 11th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2005, Santiago de Compostela,

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In our clinical example, the appearance of the pattern described over Lead II does not imply a sinusal beat if in aVR P wave is positive. Furthermore, the MFTP model is able to explicitly represent the hierarchy of abstraction levels that the expert employs to reason about the system. This enables detailed explanations of the reasons behind the occurrence or nonoccurrence of a pattern to be given. Going back to the example, the independent representation of the onset of the P wave and of the QRS complex makes it possible to reason over whether the non-occurrence of the pattern was caused by an abnormal origin of the beat (P wave negative in II), or whether there has been a first-degree blockage (excessive distance between the P wave and the QRS complex) or a second-degree one (the P wave is not followed by a QRS complex).

Operations Research 28 (1980) 1130–1145 4. Beasley, J. : Obtaining Test Problems via Internet. Journal of Global Optimization 8 (1996) 429–433 5. Chu, P. , Beasley, J. : A Genetic Algorithm for the Multidimensional Knapsack Problem. Journal of Heuristics 4 (1998) 63–86 6. : Heuristics and Reduction Methods for Multiple Constraints 0–1 Linear Programming Problems. Europena Journal of Operationa Research 24 (1986) 206–215 7. : Allocation of Databases and Processors in a Distributed Computing System.

Given that the MFTP model is based on the formalism of constraint networks, comparing an MFTP with P is formally equivalent to solving a CSP [1], where the domains of the variables are determined by P. Definition 4. , Asns } to all the significant points of the pattern that satisfies the set of constraints that make up M, with a degree greater than zero. The degree of satisfaction of a solution A is given by: π M (A) = min{ min M MM h ∈W M M M {π Mh (AMh )}, min Rk {π Rk (ARk )}} (1) ∈RM Where AMh and ARk are the projection of A over the set of significant points Rk involved in MM is the degree of satisfaction of h and in Rk , respectively.

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