This paper presents a novel approach to model–based diagnosis. The approach addresses the two main problems that have prevented model–based diagnostic techniques from being widely used: computational complexity of abduction and inadequacies of device models. A model for automated diagnosis is defined that combines (1) deduction to rule out hypotheses, (2) abduction to generate hypotheses, and (3) induction to recall past experiences and account for potential errors in the device models. A review of the three forms of inference is provided, as well as a detailed analysis of the relationship between case–based reasoning and induction. The proposed model for diagnosis is used to characterize diagnostic errors and relate them to different types of errors in the device models. Experimental results are then described and used to assert the practicality and the usefulness of the approach. The model presented in this paper yields a practical method for solving hard diagnostic problems at a reasonable computational cost and provides a theoretical basis for overcoming the problem of partially incorrect device models.

Nial is a programming language designed around a mathematical treatment of data as nested arrays. A goal of the research described is to integrate within Nial a functional style of programming based on the theory of arrays with the declarative capabilities of a logic programming environment. This is partially accomplished by storing logic clauses as arrays which can be manipulated using logic clauses. Arrays as terms are considered as part of the syntax of the clauses. The approach to logic programming is based on providing a flexible environment for experimenting with full clausal or Horn clause logic. A variety of predefined control strategies and the capability for user-defined control strategies have been provided. The expressive capabilities of combining logic and functional programming styles provides a suitable language for many application areas. The philosophy and design behind a combined logic/database model used to prototype a knowledge-based systems application are described.>