A Brief Discussion about the Credal Semantics for Probabilistic Answer Set Programs

Among the different logic-based programming languages, Answer Set Programming has emerged as an effective paradigm to solve complex combinatorial tasks. Since most of the real-world data are uncertain, several semantics have been proposed to extend Answer Set Programming to manage uncertainty, where rules are associated with a weight, or a probability, expressing a degree of belief about the truth value of certain atoms. In this paper, we focus on one of these semantics, the Credal Semantics, highlight some of the differences with other proposals, and discuss some possible future works.