Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Complex software systems typically involve features like time, concurrency and probability, where probabilistic computations play an increasing role. It is challenging to formaliz...
Huibiao Zhu, Shengchao Qin, Jifeng He, Jonathan P....
The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have...
Angelika Kimmig, Bart Demoen, Luc De Raedt, V&iacu...
— Serious efforts to develop computerized systems for natural language understanding and machine translation have taken place for more than half a century. Some successful system...