Abstract:Abstract.This paper describes a new algorithm for planing with incomplete information and conflicts. The given planing problem has two optimazation criteria: maximize the utility and minimize the conflicts of the plan. In order to achieve the first optimization goal by utility with incomplete data we build a clustering algorithm based on a fuzzy comparison method for intervals. To minimize the.conflicts while keeping a light utility, we apply genetic algorithm. The experiments show that a good balance is achie… Show more
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