We study the empirical meaning of randomness with respect to a family of probability distributions P, where is a real parameter, using algorithmic randomness theory. In the case w...
Probabilistic expert systemsbased on Bayesian networks(BNs)require initial specification both a qualitative graphical structure and quantitative assessmentof conditional probabili...
We introduce ProbLog, a probabilistic extension of Prolog. A ProbLog program defines a distribution over logic programs by specifying for each clause the probability that it belo...
Traditional scenario of probabilistic modelling is directed at generating samples having a given probability distribution. We argue that this scenario is impracticable for image m...
Real Options for Project Schedules (ROPS) has three recursive sampling/optimization shells. An outer Adaptive Simulated Annealing (ASA) optimization shell optimizes parameters of ...