2013/03/06 by Jürg Kohlas, Kohlas, Jurg, Paul-André Monney +1
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.1303.1512
openalex publication_date 2013/03/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then it is placed into the framework of evidence theory. Several authors like Laskey, Lehner (1989) and Provan (1990) already proposed a similar point of view, but the first paper is not as much concerned with mathematical foundations, and Provan's paper develops into a different direction. Here we thoroughly develop and present the mathematical foundations of this theory, together with computational methods adapted from Reiter, De Kleer (1987) and Inoue (1992). Finally, recently proposed techniques for computing degrees of support are presented.