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Cet article décrit une approche de la modélisation d'un système
d'acteurs, particulièrement adaptée à la modélisation des
entreprises, fondée sur la théorie des jeux [11] et sur
l'optimisation par apprentissage du comportement de ces acteurs. Cette
méthode repose sur la combinaison de trois techniques : la simulation
par échantillonnage (Monte-Carlo), la théorie des jeux pour ce qui
concerne la recherche d'équilibre entre les stratégies, et les
méthodes heuristiques d'optimisation locale,...
Nowadays, nature–inspired metaheuristic algorithms are most powerful optimizing algorithms for solving the NP–complete problems. This paper proposes three approaches to find near–optimal Golomb ruler sequences based on nature–inspired algorithms in a reasonable time. The optimal Golomb ruler (OGR) sequences found their application in channel–allocation method that allows suppression of the crosstalk due to four–wave mixing in optical wavelength division multiplexing systems. The simulation results...
In one if his paper Luo transformed the problem of sum-fuzzy rationality into artificial learning procedure and gave an algorithm which used the learning rule of perception. This paper extends the Luo method for finding a sum-fuzzy implementation of a choice function and offers an algorithm based on the artificial learning procedure with fixed fraction. We also present a concrete example which uses this algorithm.
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