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<ref>[http://www.mdatechnology.net/techprofile.aspx?id=227 ]: MDA Technology Applications Program web site</ref>
<ref>[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4274797]: Cangelosi, A.; Tikhanoff, V.; Fontanari, J.F.; Hourdakis, E., Integrating Language and Cognition: A Cognitive Robotics Approach, Computational Intelligence Magazine, IEEE, Volume 2, Issue 3, Aug. 2007 Page(s):65 - 70</ref>
<ref>[http://spie.org/x648.xml?product_id=521387&showAbstracts=true&origin_id=x648]: Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense III (Proceedings Volume),Editor(s): Edward M. Carapezza, Date: 15 September 2004,ISBN: 9780819453266, See Chapter: ''Counter-terrorism threat prediction architecture''</ref>
This framework has been developed by [[Leonid Perlovsky]] at the [[AFRL]]. NMF is interpreted as a mathematical description of mind’s mechanisms, including [[concepts]], [[emotions]], [[instincts]], [[imagination]], [[thinking]], and [[understanding]]. NMF is a multi-level, hetero-hierarchical system. At each level in NMF there are concept-models encapsulating the knowledge; they generate so-called top-down signals, interacting with input, bottom-up signals. These interactions are governed by dynamic equations, which drive concept-model learning, adaptation, and formation of new concept-models for better correspondence to the input, bottom-up signals.
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