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International Conference on Artificial General Intelligence

AGI 2019: Artificial General Intelligence pp 121–131Cite as

Mental Actions and Modelling of Reasoning in Semiotic Approach to AGI

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11654))

Abstract

The article expounds the functional of a cognitive architecture Sign-Based World Model (SBWM) through the algorithm for the implementation of a particular case of reasoning. The SBWM architecture is a multigraph, called a semiotic network with special rules of activation spreading. In a semiotic network, there are four subgraphs that have specific properties and are composed of constituents of the main SBWM element – the sign. Such subgraphs are called causal networks on images, significances, personal meanings, and names. The semiotic network can be viewed as the memory of an intelligent agent. It is proposed to divide the agent’s memory in the SBWM architecture into a long-term memory consisting of signs-prototype, and a working memory consisting of signs-instance. The concept of elementary mental actions is introduced as an integral part of the reasoning process. Examples of such actions are provided. The performance of the proposed reasoning algorithm is considered by a model example.

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Acknowledgements

The reported study was supported by RFBR, research Projects No. 18-07-01011 and No. 18-29-22027.

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Authors and Affiliations

  1. National Research University Higher School of Economics, Moscow, Russia

    Alexey K. Kovalev

  2. Artificial Intelligence Research Institute, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia

    Alexey K. Kovalev & Aleksandr I. Panov

  3. Moscow Institute of Physics and Technology, Moscow, Russia

    Aleksandr I. Panov

Authors
  1. Alexey K. Kovalev
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  2. Aleksandr I. Panov
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Corresponding author

Correspondence to Aleksandr I. Panov .

Editor information

Editors and Affiliations

  1. Temple University, Philadelphia, PA, USA

    Patrick Hammer

  2. University of Memphis, Memphis, TN, USA

    Pulin Agrawal

  3. SingularityNET, Tai Po, Hong Kong, China

    Ben Goertzel

  4. SingularityNET, Alamosa, CO, USA

    Matthew Iklé

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Kovalev, A.K., Panov, A.I. (2019). Mental Actions and Modelling of Reasoning in Semiotic Approach to AGI. In: Hammer, P., Agrawal, P., Goertzel, B., Iklé, M. (eds) Artificial General Intelligence. AGI 2019. Lecture Notes in Computer Science(), vol 11654. Springer, Cham. https://doi.org/10.1007/978-3-030-27005-6_12

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  • DOI: https://doi.org/10.1007/978-3-030-27005-6_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27004-9

  • Online ISBN: 978-3-030-27005-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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