iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
Biochemical pathways or networks are generic representations used to model many different types of complex functional and physical interactions in biological systems. Models based ...
Patrick Doherty, Steve Kertes, Martin Magnusson, A...
Representing and reasoning about time dependent information is a key research issue in many areas of computer science and artificial intelligence. One of the best known and widely...
This paper addresses a major weakness of current technologies for the Semantic Web, namely the lack of a principled means to represent and reason about uncertainty. This not only h...
Paulo Cesar G. da Costa, Kathryn B. Laskey, Kennet...