Business Rules Uncertainty Management with Probabilistic Relational Models

May 23, 2016 at 9:55:44 AM
New CS Department,
Engineering Dr,
11794 Stony Brook, NY
From Jul 8, 2016, 12:00 PM
To Jul 8, 2016, 12:30 PM
A paper by Hamza AGLI (IBM France), Philippe BONNARD (IBM France), Christophe GONZALES (Sorbonne Universite) and Pierre-Henri WUILLEMIN (Sorbonne Universite)
Abstract. Object-oriented Business Rules Management Systems (OO-BRMS) are a complex applications platform that provides tools for automating day-to-day business decisions. To allow more sophisticated and realistic decision-making, these tools must enable Business Rules (BRs) to handle uncertainties in the domain. For this purpose, several approaches have been proposed, but most of them rely on heuristic models that unfortunately have shortcomings and limitations. In this paper we present a solution allowing modern OO-BRMS to effectively integrate probabilistic reasoning for uncertainty management. This solution has a coupling approach with Probabilistic Relational Models (PRMs) and facilitates the interoperability, hence, the separation between business and probabilistic logic. We apply our approach to an existing BRMS and discuss implications of the knowledge base dynamicity on the probabilistic inference.