MECHANIZING SHARED CONFIGURATION AND DIAGNOSIS THEORIES THROUGH CONSTRAINT LOGIC PROGRAMMING

Configuration and diagnosis problem-solvers are commonly championed as successes of applied artificial intelligence techniques. A common pro blem is that problem-solvers typically encode task-specific representa tion assumptions and simplifications in their domain theories, hinderi ng the reuse of the domain theories between the problem-solvers. While model-based reasoning techniques have been shown to provide an intere sting approach to sharing component and device specifications, their r espective mechanisations are generally too inefficient. We show how co nstraint logic programming languages provide a flexible environment in which constraint-based specifications can be effectively shared and e fficiently mechanised by exploiting constraint solving and propagation techniques tightly integrated with the backtracking search mechanism of logic programming languages. A component specification language is presented and the mappings from the language to the constraint system and strategies for guiding the search are defined for the respective p roblem-solvers. (C) 1998 Elsevier Science Inc. All rights reserved.