Convergence of a modified algorithm of fast probabilistic modeling

Authors:
D. A. Gobov
Affiliations:
V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
Venue:
Cybernetics and Systems Analysis
Year:
2008

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Abstract

The convergence of fast probabilistic modeling algorithms (G-algorithms) is analyzed. A G-algorithm is modified based on a new probabilistic approach, used to reject points in the neighborhood of the current solution. A theoretically justified estimate of the rate of convergence, independent of the initial approximation, is obtained for this modification. A computational experiment is conducted to compare the performance of the modified G-algorithm with that of the classical one.