26 citations · 33 across the 4 of their papers we have counts for
4 papers
Encoding Markov Logic Networks in Possibilistic Logic
Ondrej Kuzelka, Jesse Davis, Steven Schockaert
Markov logic uses weighted formulas to compactly encode a probability distribution over possible worlds. Despite the use of logical formulas, Markov logic networks (MLNs) can be di…
Realizing RCC8 networks using convex regions
Steven Schockaert, Sanjiang Li
RCC8 is a popular fragment of the region connection calculus, in which qualitative spatial relations between regions, such as adjacency, overlap and parthood, can be expressed. Whi…
Possibilistic Answer Set Programming Revisited
Kim Bauters, Steven Schockaert, Martine De Cock +1
Possibilistic answer set programming (PASP) extends answer set programming (ASP) by attaching to each rule a degree of certainty. While such an extension is important from an appli…
Reducing Fuzzy Answer Set Programming to Model Finding in Fuzzy Logics
Jeroen Janssen, Steven Schockaert, Dirk Vermeir +1
In recent years answer set programming has been extended to deal with multi-valued predicates. The resulting formalisms allows for the modeling of continuous problems as elegantly…