Fuzzy Answer Set Programming
Jeroen Janssen, Steven Schockaert, Dirk Vermeir, Martine De Cock · Atlantis computational intelligence systems · 2012
In the previous chapter we introduced ASP, a language that allows to model combinatorial problems in a declarative manner. Unfortunately, ASP is limited to expressing problems in boolean logic. Many interesting applications require different logics, however. For example, suppose we want to write an ASP program that finds the disease from which a patient is suffering, given a set of his symptoms as the input. Obviously the output of this program will be uncertain, as certain symptoms may occur in 80% of the patients, while others may only occur in about 30%. Hence, the answer sets and the computation of the answer sets should reflect this in some way. This can be done by extending the ASP semantics with a theory of uncertainty, such as possibility or probability theory.