Abstract
The paper explores the implementation of rule-based pattern-directed inference systems on parallel computers. The paper discusses one of these approaches in detail, the use of a graph-reduction machine such as ALICE. The technique is illustrated through two example domains: automobile fault diagnosis and organic psychiatric mental disorders. The paper discusses extensions to the graph reduction technique as applied to knowledge-based systems, including partitioning, time considerations and input data types. The paper shows that the graph-reduction technique has significant advantages for knowledge-based system implementation over conventional approaches, and it demonstrates that this programming style is amenable to knowledge engineering domains.
