ABSTRACT
Soar is an architecture for general intelligence that has been proposed as a unified theory of human cognition (UTC) (Newell, 1989) and has been shown to be capable of supporting a wide range of intelligent behavior (Laird, Newell & Rosenbloom, 1987; Steier el al., 1987). Polk & Newell (1988) showed that a Soar theory could account for human data in syllogistic reasoning. In this paper, we begin to generalize this theory into a unified theory of immediate reasoning based on Soar and some assumptions about subjects' representation and knowledge. The theory, embodied in a Soar system (IR-Soar), posits three basic problem spaces (comprehend, test-proposition, and build-proposition) that construct annotated models and extract knowledge from them, learn (via chunking) from experience and use an attention mechanism to guide search. Acquiring task specific knowledge is modeled with the comprehend space, thus reducing the degrees of freedom available to fit data. The theory explains the qualitative phenomena in four immediate reasoning tasks and accounts for an individual's responses in syllogistic reasoning. It represents a first step toward a unified theory of immediate reasoning and moves Soar another step closer to being a unified theory of all of cognition.
