International Journal of Intelligent Information Systems

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Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents

Received: Sep. 11, 2020    Accepted: Sep. 24, 2020    Published: Sep. 29, 2020
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Abstract

At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified agents with strong artificial intelligence based on communicative-associative logic by recurring development of professional skills, increasing visual, sound, subject, spatial and temporal sensitivity. For this purpose several diversifiable agents that try to get the same conclusion will give a more accurate result, so several diversifiable agents are combined into an ensemble. Then, based on the criteria of utility and preference, the final result is obtained based on the conclusions of diversifying agents. This approach increases accuracy. Bagging and Boosting techniques are used to form ensembles. Bagging is a combination of independent diversifiable agents by averaging patterns (weighted average, majority vote, or normal average). Boosting is the construction of ensembles of diversifiable agents consistently. The idea here is that the next agent will consider the errors of the previous agent. Due to the fact that diversifiable agents take into account errors committed by previous agents, it takes less time to get to a real response. The combination of Bagging and Boosting decision-making methods allows the development of intelligent artificial intelligence by ensembles of diversified agents. Cognitive virtual smart artificial intelligence becomes smarter through the accumulated professional experience of high-tech skills, competencies and knowledge, having increased visual, sound, subject, spatial and temporal sensitivity. Many researchers believe that the information technology industry is on the verge of a transition to smart universal artificial intelligence. The information technology industry is trying to find the boundaries of smart artificial intelligence. Standardization of strong artificial intelligence and the use of ensembles of intelligent compatible diversified agents will help to find boundaries in which smart artificial intelligence will benefit humanity and not harm.

DOI 10.11648/j.ijiis.20200904.11
Published in International Journal of Intelligent Information Systems ( Volume 9, Issue 4, August 2020 )
Page(s) 24-34
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Smart Artificial Intelligence, Communicative Associative Logic, Preference and Utility Criteria, Ensembles of Diversified Agents

References
[1] Evgeniy Bryndin. Practical Development of Creative Life-Saving Strong Artificial Intelligence. Communications, Vol.7, No.1, 2019. Pages: 31-39.
[2] Stewart Russell, Peter Norvig. Artificial Intelligence: Modern Approach. Williams, 2019. 1408 p. ISBN: 978-5-8459-1968-7
[3] Wu Jun. Research on the Framework of Smart City Operating System Based on New ICTs. American Journal of Artificial Intelligence. Volume 4, Issue 1, June 2020, Pages: 36-41. doi: 10.11648/j.ajai.20200401.14.
[4] Evgeniy Bryndin. System retraining to professional competences of cognitive robots on basis of communicative associative logic of technological thinking. International Robotics Automation Journal. 2019; 5 (3.): 112‒119.
[5] Evgeniy Bryndin. Human Digital Doubles with Technological Cognitive Thinking and Adaptive Behaviour. Software Engineering, Volume 7, Issue 1, 2019. P. 1-9.
[6] CRONEMBERGER F, GIL-GARCIA J R. Big data and analytics as strategies to generate public value in smart cities: proposing an integrative framework [M]. Switzerland: Springer Nature, 2019.
[7] Evgeniy Bryndin. Development of Artificial Intelligence by Ensembles of Virtual Agents on Technological Platforms. COJ Technical & Scientific Research. 2 (4). 2020. Pages: 1-8.
[8] Evgeniy Bryndin. Development of artificial intelligence by ensembles of virtual diversification agents. International Journal of Research in Engineering. Volume 2; Issue 1; 2020; Page 08-14.
[9] Raja Muhammad Asif Zahoor, Khan, Junaid Ali, Qureshi I. M. (2019) Evolutionary Computational Intelligence in Solving the Fractional Differential Equations. 11th Asian Conference, ACIIDS 2019, Yogyakarta, Indonesia, April 8–11, 2019, Proceedings, Part I, 231-240.
[10] Evgeniy Bryndin. Development of Artificial Intelligence by Ensembles of Virtual Agents with Mobile Interaction. Automation, Control and Intelligent Systems. Volume 8; Issue 1. 2020. Pages: 1-8.
[11] Oleg Vasylovych Moroz, Model of Self-organizing Knowledge Representation and Organizational Knowledge Transformation, American Journal of Artificial Intelligence. Vol. 4, No. 1, 2020, pp. 1-19. doi: 10.11648/j.ajai.20200401.11.
[12] ISO/IEC JTC 1/SC 42/WG 4 Use cases and applications Convenorship: JISC (Japan). 2019-12-23. https://isotc.iso.org/livelink/livelink/open/jtc1sc42wg4
[13] Evgeniy Bryndin. Standardization of Artificial Intelligence for the Development and Use of Intelligent Systems. Advances in Wireless Communications and Networks. Volume 6, Issue 1, 2020, pp. 1-9.
[14] Evgeniy Bryndin. Safe Interaction of Technocratic Societies Through Standardy Ensemble of Intellectual Virtual Agents. Control Science and Engineering. Volume 4, Issue 1, 2020, pp. 8-15.
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  • APA Style

    Evgeniy Bryndin. (2020). Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents. International Journal of Intelligent Information Systems, 9(4), 24-34. https://doi.org/10.11648/j.ijiis.20200904.11

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    ACS Style

    Evgeniy Bryndin. Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents. Int. J. Intell. Inf. Syst. 2020, 9(4), 24-34. doi: 10.11648/j.ijiis.20200904.11

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    AMA Style

    Evgeniy Bryndin. Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents. Int J Intell Inf Syst. 2020;9(4):24-34. doi: 10.11648/j.ijiis.20200904.11

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  • @article{10.11648/j.ijiis.20200904.11,
      author = {Evgeniy Bryndin},
      title = {Communicative-Associative Development of Smart Artificial Intelligence by Criteria with Help of Ensembles of Diversified Agents},
      journal = {International Journal of Intelligent Information Systems},
      volume = {9},
      number = {4},
      pages = {24-34},
      doi = {10.11648/j.ijiis.20200904.11},
      url = {https://doi.org/10.11648/j.ijiis.20200904.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijiis.20200904.11},
      abstract = {At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified agents with strong artificial intelligence based on communicative-associative logic by recurring development of professional skills, increasing visual, sound, subject, spatial and temporal sensitivity. For this purpose several diversifiable agents that try to get the same conclusion will give a more accurate result, so several diversifiable agents are combined into an ensemble. Then, based on the criteria of utility and preference, the final result is obtained based on the conclusions of diversifying agents. This approach increases accuracy. Bagging and Boosting techniques are used to form ensembles. Bagging is a combination of independent diversifiable agents by averaging patterns (weighted average, majority vote, or normal average). Boosting is the construction of ensembles of diversifiable agents consistently. The idea here is that the next agent will consider the errors of the previous agent. Due to the fact that diversifiable agents take into account errors committed by previous agents, it takes less time to get to a real response. The combination of Bagging and Boosting decision-making methods allows the development of intelligent artificial intelligence by ensembles of diversified agents. Cognitive virtual smart artificial intelligence becomes smarter through the accumulated professional experience of high-tech skills, competencies and knowledge, having increased visual, sound, subject, spatial and temporal sensitivity. Many researchers believe that the information technology industry is on the verge of a transition to smart universal artificial intelligence. The information technology industry is trying to find the boundaries of smart artificial intelligence. Standardization of strong artificial intelligence and the use of ensembles of intelligent compatible diversified agents will help to find boundaries in which smart artificial intelligence will benefit humanity and not harm.},
     year = {2020}
    }
    

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    Y1  - 2020/09/29
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    AB  - At the present stage of the development of information technologies, cognitive robotization, digital doubles and artificial intelligence systems, their synergy allows us to begin to form rational smart artificial intelligence in virtual space. Cognitive virtual smart artificial intelligence author proposes developing by ensembles of diversified agents with strong artificial intelligence based on communicative-associative logic by recurring development of professional skills, increasing visual, sound, subject, spatial and temporal sensitivity. For this purpose several diversifiable agents that try to get the same conclusion will give a more accurate result, so several diversifiable agents are combined into an ensemble. Then, based on the criteria of utility and preference, the final result is obtained based on the conclusions of diversifying agents. This approach increases accuracy. Bagging and Boosting techniques are used to form ensembles. Bagging is a combination of independent diversifiable agents by averaging patterns (weighted average, majority vote, or normal average). Boosting is the construction of ensembles of diversifiable agents consistently. The idea here is that the next agent will consider the errors of the previous agent. Due to the fact that diversifiable agents take into account errors committed by previous agents, it takes less time to get to a real response. The combination of Bagging and Boosting decision-making methods allows the development of intelligent artificial intelligence by ensembles of diversified agents. Cognitive virtual smart artificial intelligence becomes smarter through the accumulated professional experience of high-tech skills, competencies and knowledge, having increased visual, sound, subject, spatial and temporal sensitivity. Many researchers believe that the information technology industry is on the verge of a transition to smart universal artificial intelligence. The information technology industry is trying to find the boundaries of smart artificial intelligence. Standardization of strong artificial intelligence and the use of ensembles of intelligent compatible diversified agents will help to find boundaries in which smart artificial intelligence will benefit humanity and not harm.
    VL  - 9
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Author Information
  • Research Department, Research Center "Natural Informatics", Novosibirsk, Russia

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