Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
A compositional method for estimating software reliability of many threaded programs is developed. The method uses estimates of the reliability of individual modules and the proba...
Abstract. This paper introduces Higher-Order Bayesian Networks, a probabilistic reasoning formalism which combines the efficient reasoning mechanisms of Bayesian Networks with the...
Logic-based probabilistic models (LBPMs) enable us to handle problems with uncertainty succinctly thanks to the expressive power of logic. However, most of LBPMs have restrictions...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...