A Metacognitive Classifier Using a Hybrid ACT-R/Leabra Architecture

Yury Vinokurov, Christian Lebiere, Seth A. Herd, Randall C. O'Reilly

Abstract: We present a metacognitive classifier implemented within a hybrid architecture that combines the strengths of two existing, mature cognitive architectures: ACT-R and Leabra. The classification of a set of items into previously seen and novel categories (TRAIN and TEST, respectively) is carried out in ACT-R using metacognitive signals supplied by Leabra. The resulting system performance is analyzed as a function of various architectural parameters, and future directions of research are discussed.