Structured Modeling Language for Automated Modeling in Causal Networks

Abstract

The paper presents a structured modeling language (SML) and a relational database framework for specification and automated generation of causal models. The framework describes a relational database scheme for encoding a library of causal network templates modeling the basic components in a modeling domain . SML provides a formal language for specifying models as structured components that can be composed from the basic components. The language enables specification of models as l?arameterized relational queries that can be mstantiated for specific mod el instances. The paper describes an algorithm that , given a library and a sp ec ification, computes a causal model in time and space linear in the number of basic components. Th e algorithm enables model reuse by combining mod el fragments from the template library to compose new models. The present automated modeling approach has been implemented using the structured query language (SQL) and a relational database environment. The approach has been successfully used for modeling an automated work-cell in a real-life digital manufacturing application.