Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models

Abstract. Logical Bayesian Networks (LBNs) have recently been introduced as another language for knowledge based model construction of Bayesian networks, besides existing languages such as Probabilistic Relational Models (PRMs) and Bayesian Logic Programs (BLPs). The original description of LBNs introduces them as a variant of BLPs and discusses the differences with BLPs but still leaves room for a deeper discussion of the relationship between LBNs and BLPs. Also the relationship to PRMs was not treated in much detail. In this paper, we first give a more compact and clear definition of LBNs. Next, we describe in more detail how PRMs and BLPs relate to LBNs. Like this we not only see what the advantages and disadvantages of LBNs are with respect to PRMs and BLPs, we also gain more insight into the relationships between PRMs and BLPs.

• Type: Conference
• Year: 2005
• Where: ILP
• Authors: Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
• Keywords: Bayesian Logic Programs, Bayesian Networks, ILP 2005, Logical Bayesian Networks