R1-Soar: An Experiment in Knowledge-Intensive Programming in a Problem-Solving Architecture

TLDR

Soar encodes knowledge in problem spaces, enabling first‑principles reasoning. The paper reports an experiment in knowledge‑intensive programming within the Soar problem‑solving architecture. The experiment employs expertise rules that guide searches and can be programmed or learned via chunking, and demonstrates the approach on the computer‑system configuration task performed by the expert system R1.

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.