Commonsense reasoning about causality: deriving behavior from structure
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Compositional modeling: finding the right model for the job
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Artificial Intelligence
Theory of Relational Databases
Theory of Relational Databases
Diagnosing tree-decomposable circuits
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Object-oriented Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Network fragments: representing knowledge for constructing probabilistic models
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Network engineering for complex belief networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
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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 parameterized relational queries that can be instantiated for specific model instances. The paper describes an algorithm that, given a library and a specification, computes a causal model in time and space linear in the number of basic components. The algorithm enables model reuse by combining model 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.