title: R1-soar: an experiment in knowledge-intensive programming in a problem-solving architecture.
abstract: This paper presents an experiment in knowledge-intensive programming within a general problem-solving production-system architecture called Soar. In Soar, knowledge is encoded within a set of problem spaces, which yields a system capable of reasoning from first principles. Expertise consists of additional rules that guide complex problem-space searches and substitute for expensive problem-space operators. The resulting system uses both knowledge and search when relevant. Expertise knowledge is acquired either by having it programmed, or by a chunking mechanism that automatically learns new rules reflecting the results implicit in the knowledge of the problem spaces. The approach is demonstrated on the computer-system configuration task, the task performed by the expert system R1.
authors.affiliation: Departments of Computer Science and Psychology, Stanford University, Stanford, CA 94305.
authors.forename: P S
authors.initials: PS
authors.lastname: Rosenbloom
authors.forename: J E
authors.initials: JE
authors.lastname: Laird
authors.forename: J
authors.initials: J
authors.lastname: McDermott
authors.forename: A
authors.initials: A
authors.lastname: Newell
authors.forename: E
authors.initials: E
authors.lastname: Orciuch