Constraint-Based Reasoning on Probabilistic Choice Operators
Abstract
Probabilistic Concurrent Constraint Programming (PCCP) extends concurrent constraint languages with a probabilistic choice operator. This operator has proved to be useful in implementing randomized algorithms as well as stochastic processes. In this report, we present a filtering algorithm dedicated to the probabilistic choice operator which permits to address new kind of applications where probabilistic choices are partially known. This filtering algorithm helps to deduce information on the possible values of the probabilistic choice without requiring its full valuation. An implementation under the form of a library of SICStus Prolog is presented.
Origin : Files produced by the author(s)
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