Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

Authors

  • Alla A Mamaeva Dubna State University, Russia INESYS LLC (EFKO GROUP), Russia
  • Andrey V Shevchenko Dubna State University, Russia INESYS LLC (EFKO GROUP), Russia
  • Sergey Victorovich Ulyanov State University “Dubna”

DOI:

https://doi.org/10.30564/aia.v2i1.1323

Abstract

The article consists of two parts. Part I shows the possibility of quantum / soft computing optimizers of knowledge bases (QSCOptKB™) as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface. In particular, case, the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™ and QCOptKB™ sophisticated toolkit. Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described. The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown. Developed information technology examined with special (difficult in diagnostic practice) examples emotion state estimation of autism children (ASD) and dementia and background of the knowledge bases design for intelligent robot of service use is it. Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated. 

Keywords:

neural interface； computational intelligence toolkit； intelligent control system； deep machine learning； emotions； quantum soft computing optimizer

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How to Cite

Mamaeva, A. A., Shevchenko, A. V., & Ulyanov, S. V. (2020). Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach. Artificial Intelligence Advances, 2(1), 1–30. https://doi.org/10.30564/aia.v2i1.1323

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Vol. 2 , Iss. 1 (April 2020)

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Article

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.

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