Artificial Intelligence

   

Topological Clustering as a Method of Control for Certain Critical-Point Sensitive Systems

Authors: Martin J. Dudziiak

New methods can provide more sensitive modeling and more reliable control, through use of dynamically-alterable local neighborhood clusters comprised of of the state-space parameters most disposed to be influential in non-linear systemic changes. Particular attention is directed to systems with extreme non-linearity and uncertainty in measurement and in control communications (e.g., micro-scalar, remote and inaccessible to real-time control). An architecture for modeling based upon topological similarity mapping principles is introduced as an alternative to classical Turing machine models including new “quantum computers.”

Comments: 6 Pages. submitted to CoDIT 2018 (Thessaloniki, Greece, April 2018)

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[v1] 2017-12-05 14:07:08

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