Assessment of Model Generative Reasoning for Use in the Intelligence ProductionPerformance Model

摘要

This report assesses the applicability of the enhanced-Model Generative Reasoning(e-MGR) problem-solving architecture for supplying the information processing mechanisms for the Intelligence Production Performance Model (IPPM). The independent variables controlling error performance in the IPPM have analogical relationships with the operators in the e-MGR. A software demonstration illustrates the integration of e-MGR and IPPM to produce context changes resulting from errors in hypothesis generation. The e-MGR can provide a suitable set of mechanisms for augmenting the IPPM. The e-MGR mechanisms can dynamically sketch the etiology of errors and their decision efforts.