AiGERM: A logic programming front end for GERM

AiGerm (Artificially Intelligent Graphical Entity Relation Modeler) is a relational data base query and programming language front end for MCC (Mission Control Center)/STP's (Space Test Program) Germ (Graphical Entity Relational Modeling) system. It is intended as an add-on component of the Germ system to be used for navigating very large networks of information. It can also function as an expert system shell for prototyping knowledge-based systems. AiGerm provides an interface between the programming language and Germ

Foundation: Transforming data bases into knowledge bases

One approach to transforming information stored in relational data bases into knowledge based representations and back again is described. This system, called Foundation, allows knowledge bases to take advantage of vast amounts of pre-existing data. A benefit of this approach is inspection, and even population, of data bases through an intelligent knowledge-based front-end

An information-based approach to integrating empirical and explanation-based learning

We describe a new approach to integrating explanation-based and empirical learning methods for learning relational concepts. The approach uses an information-based heuristic to evaluate components of a hypothesis that are proposed either by explanation-based or empirical methods. Providing domain knowledge to the integrated system can decrease the amount of search required during learning and increase the accuracy of learned concepts, even when the domain knowledge is incorrect and incomplete and there is noise in the training data

Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed

Knowledge Transformations between Frame Systems and RDB Systems

For decades, researchers in knowledge representation (KR) have argued for and against various choices in KR formalisms, such as Rules, Frames, Semantic nets, and Formal logic. In this paper, we present a set of transformations that can be used to move knowledge across two fundamentally different KR formalisms: Frame-based systems and Relational database systems (RDBs). We also describe partial implementations of these transformations for a specific pair of such systems: Protégé and the Postgres RDB system

Interval computations with BK-products of fuzzy relations in diagnostic knowledge-based system CLINAID

CLINAID is a medical knowledge-based system that uses fuzzy relational structures for both knowledge representation and inference. The system can deal with multiple body systems. Interval-based fuzzy logics employed in CLINAID make it possible to deal efficiently with multiplicity of contexts that appear in medical decision making involving risk and uncertainty. A particular emphasis is placed on the description of the involvement of fuzzy triangle and square relational products that play a significant role in our approach.peer-reviewe