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

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

This booklet 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 offered including an invited paper have been rigorously chosen in the course of rounds of reviewing and development from an preliminary overall of 147 submissions. The papers span the full spectrum of synthetic intelligence from foundational and theoretical concerns to complicated purposes in a variety of fields.

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A significant point Xij = < Vij , Tij > represents an unknown value Vij for P j at an unknown temporal instant Tij . In the absence of constraints, Vij and j j Tij may take any precise value v[k] and tj[k] , respectively, where (v[k] , tj[k] ) ∈ P j . , Aji = (v[k] , tj[k] ). We define a general fuzzy constraint between a set of significant points, providing a computable support for soft descriptions of the form of a signal. Definition 2. , Xigg ). 34 A. Otero et al. Fig. 1. , Xigg . In principle, nothing restricts the form of the constraints that make up a MFTP.

M ). Each ωi will be represented as a q-bit binary substring, where q determines the desired precision of ωi ∈ (0, 1]. Definition 7. Given an MKP instance K = (n, m, p, A, b), q ∈ IN, and a representation γ ∈ {0, 1}qm of a candidate vector of surrogate multipliers ω = (ω1 , . . , ωm ) the fitness value of γ is defined as follows: f itness(γ) = f (αopt )= SR(K,ω)LP n j=1 pj αopt [j] SR(K,ω)LP (10) Remark 8. The solution αopt SR(K,ω)LP can be obtained by means of the well known greedy algorithm for one-dimensional instances of the LP–relaxed knapsack problem.

By means of π A we define a fuzzy subset A of R, which contains the possible values of A. We introduce the concept of fuzzy increment with the aim of representing quantities, such as the difference between two numbers, which may be fuzzy or not. Following Zadeh’s extension principle [6], the fuzzy increment between a pair of fuzzy numbers A and B is given by D such π D (i) = maxi=t−s min{π A (t), π B (s)}. 3 Clinical Example We use an example from the clinical domain to introduce the MFTP model: the recognition of the sinusal P wave in a multichannel electrocardiogram (ECG) recording.

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