title: Explanation of Bayesian networks and influence diagrams in Elvira.
abstract: Bayesian networks (BNs) and influence diagrams (IDs) are probabilistic graphical models that are widely used for building diagnosis- and decision-support expert systems. Explanation of both the model and the reasoning is important for debugging these models, alleviating users' reluctance to accept their advice, and using them as tutoring systems. This paper describes some explanation options for BNs and IDs that have been implemented in Elvira and how they have been used for building medical models and teaching probabilistic reasoning to pre- and postgraduate students.
authors: Department of Technology and Information Systems, University of Castilla-La Mancha, 13071 Ciudad Real, Spain. carmen.lacave@uclm.es
authors: Carmen
authors: C
authors: Lacave
authors: Manuel
authors: M
authors: Luque
authors: Francisco Javier
authors: FJ
authors: Díez
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001499:Bayes Theorem; D003198:Computer Simulation; D003661:Decision Support Techniques; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D012984:Software