{'fraction_non_alphanumeric': 0.022847100175746926, 'fraction_numerical': 0.0, 'mean_word_length': 5.551724137931035, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Metacognitive Classifier Using a Hybrid ACT-R/Leabra Architecture

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.