MIDCA: A Metacognitive, Integrated Dual-Cycle Architecture for Self-Regulated Autonomy

Abstract

This report documents research performed under ONR grant N000141210172 for the period 1 June 2012 through 31 May 2013. The goals of this research are to provide a sound theoretical understanding of the role of metacognition in cognitive architectures and to demonstrate the underlying theory through implemented computational models. During the last year, the team has been integrating existing implemented systems to form an initial architectural structure that approximates the major functions of MIDCA. These include the SHOP2 hierarchical planning system and the Meta-AQUA integrated multistrategy learning system. We have also produced substantial progress on the data-driven track of the interpretation procedure. Last year’s work on using the A-distance metric for anomaly detection has been matured, and we have collected substantial observations used in empirical evaluation. Additionally we started implementation of a neural network to induce proto-type nodes for observed anomalies, and we are developing methods to prioritize explanations and responses that have proven effective with past anomalies in proto-type categories. The data are encouraging and the research community has reacted favorably. Several new publications support our claims herein.