We have developed a computer application, called the Bayes Inference Engine, to enable us to make inferences about models of a physical object from radiographs taken of it. In the BIE calculational models are represented by a dataflow diagram that can be manipulated by the analyst in a graphical-programming environment. We demonstrate the operation of the BIE in terms of examples of two-dimensi...

We address the inverse problem of source reconstruction from a Bayesian perspective. Bayesian probability theory provides a natural and logically consistent (principled) approach for source reconstruction. To facilitate Bayesian source reconstruction, we develop an automated computational inference engine for efficient sampling from the potentially complex source parameter (or hypothesis) space...

A Distributed Network Architecture (DNA) forms the basis of many decisionsupport systems available today. Such architecture excels at providing an application environment rich in transparency, performance, and expandability (Gray and Lievano 1997). However, efforts at the Collaborative Agent Design (CAD) Research Center in San Luis Obispo, California have found that for this architecture to be ...

Parallel processing systems offer a major improvement in capabilities to AI programmers. However, at the moment, all such systems require the programmer to manage the control of parallelism explicitly, leading to an unfortunate intermixing of knowledge-level and control-level information. Furthermore, parallel processing systems differ radically, making a control regime that is effective in one...

Probabilistic networks have shown to be an important tool to work with probability-measured uncertainty. However, quality of probabilistic networks depends on a correct knowledge acquisition and modelling. KAMET is a model-based methodology designed to manage knowledge acquisition from multiple knowledge sources [1]. After this methodology is applied, a graphical model representing causal relat...

AB STRACT. The role of inferencing with uncertainty is becoming more important in rule-based expert systems (ES) , since knowledge given by a human expert is often uncertain or imprecise. We have succeeded in designing a VLSI chip which can perform an entire inference process based on fuzzy logic. The design of the VLSI fuzzy inference engine emphasizes simplicity, extensibility, and efficiency...

Expert reasoning in the natural sciences appears to make extensive use of a relatively small number of general principles and reasoning strategies, each associated with a larger number of more specific inference patterns. Using a dual declarative hierarchy to represent strategic and factual knowledge, we analyze a framework for a robust scientific reasoning engine. It is argued that such an eng...

SQUID-WS is a system utilizing semantic annotation of web services to increase the accuracy of web service discovery. Service providers and requestors specify characteristics of web service operations using a common ontology (OWL ontologies are used), and a matching engine is used to match specifications. An inference engine is used to determine whether service advertisements meet additional co...

OWL is a standard ontology language defined by W3C that is used for knowledge representation, discovery, and integration. Having a solid OWL reasoning engine inside a relational database system like Oracle is significant because 1) many relational techniques, including query optimization, compression, partitioning, and parallel execution, can be inherited and applied; and 2) relational database...