A schema for knowledge representation and its implementation in a computer-aided design and manufacturing system

Modularity in the design and implementation of expert systems relies upon cooperation among the expert systems and communication of knowledge between them. A prerequisite for an effective modular approach is some standard for knowledge representation to be used by the developers of the different modules. In this work we present a schema for knowledge representation, and apply this schema in the design of a rule-based expert system. We also implement a cooperative expert system using the proposed knowledge representation method. A knowledge representation schema is a formal specification of the internal, conceptual, and external components of a knowledge base, each specified in a separate schema. The internal schema defines the structure of a knowledge base, the conceptual schema defines the concepts, and the external schema formalizes the pragmatics of a knowledge base. The schema is the basis for standardizing knowledge representation systems and it is used in the various phases of design and specification of the knowledge base. Its main tasks are to govern the interface and communication of knowledge between expert systems as well as to support a modular approach in the design of a cooperative expert system. The schema is also used in the stages of testing, validation, and maintenance of a knowledge base. The conceptual schema is the formal specifications of the domain-dependent semantics and can be implemented using fuzzy semantics. For this purpose, an axiomatic theory of fuzzy semantics is developed and formal methods of specification of concepts using fuzzy semantics are proposed. A new model of knowledge representation based on a pattern recognition interpretation of implications is developed. This model implements the concept of linguistic variables and can, therefore, emulate human reasoning with linguistic imprecision. The test case for the proposed schema of knowledge representation is a system for computer-aided design of a man-machine interface. The core of the system is a cooperative expert system composed of two expert systems. This system applies a pattern recognition interpretation of a generalized one-variable implication with linguistic variables. A process of validation of the system is performed, including testing of the system and verification that the system is acyclic, consistent, and in compliance with its specifications.