Although traditional logic programming languages provide powerful tools for knowledge representation, they cannot deal with uncertainty information (e. g. probabilistic information). In this paper, we propose a probabilistic logic programming language by introduce probability into a general logic programming language. The work combines 4-valued logic with probability. Conditional probability can be easily represented in a probabilistic logic program. The semantics of such a probabilistic logic program i...
The purpose of this paper is to present the syntax and semantics of probabilistic logic programming to al-low for the correct representation of incomplete information. General logic programming is extended by a subintervalof [0,1] that describes the range for the conditional probability of the head of a clause given the range for the proba-bility of each atom of its body. We define the semantics (answer sets semantics) of such probabilistic logic program-ming and illustrative their applications. We also show some properties of answer sets semantics for the probabilisticlogic programs.
