Importance Sampling Monte - Carlo Algorithms for the Calculation ofDempster - Shafer Belief
نویسنده
چکیده
This paper presents importance sampling Monte-Carlo algorithms for the calculation of belief functions combination. When the connict between the evidence is not very high a simple Monte-Carlo algorithm can produce good quality estimations. For the case of highly connicting evidences a Markov chain Monte-Carlo algorithm was also proposed. In this paper, a new class of importance sampling based algorithms is presented. The performance of them is compared by experimental tests.
منابع مشابه
Markov Chain Monte-Carlo Algorithms for the Calculation of Dempster-Shafer Belief
A simple Monte-Carlo algorithm can be used to calculate Dempster-Shafer belief very efficiently unless the conflict between the evidences is very high. This paper introduces and explores Markov Chain Monte-Carlo algorithms for calculating Dempster-Shafer belief that can also work well when the conflict is high.
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