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Fuzzy Approach to Explainable Artificial Intelligence

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15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022 (ICAFS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 610))

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Abstract

The widespread introduction of artificial intelligence systems in all areas of human activity imposes requirements of responsibility on these systems. Systems operating in critical areas such as healthcare, economics, and security systems based on artificial neural network models should have an explanatory apparatus to be able to evaluate not only the recognition, prediction, or recommendation accuracy familiar to everyone, but also to show the algorithm for getting result of neural network working. In this paper, we investigate methods of explainable artificial intelligence for rules extraction from artificial neural networks, which are based on the fuzzy logic.

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Acknowledgement

The paper is partially supported be the grants RFBR 20-7-00770 “Facing Fundamental Problems of Constructing “Understanding” Cognitive Agents, Multi-Agent Systems and Artificial Societies on the Basis of Synergetic Artificial Intelligence Approaches, Information Granulation Techniques, Dynamic Bipolar Scales and Dialogical Worlds” and RSCF 22-71-10112 “Hybrid Decision Support Models Based on Augmented Artificial Intelligence, Cognitive Modeling and Fuzzy Logic in Problems of Personalized Medicine”.

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Authors and Affiliations

  1. Federal Research Centre of Informatics and Computer Science of RAS, Moscow, Vavilova, 42, Moscow, Russia

    Alexey Averkin

  2. Educational and Scientific Laboratory of Artificial Intelligence, Neuro-technologies and Business Analytics, Plekhanov Russian University of Economics, Stremyanny Lane, 36, Moscow, Russia

    Alexey Averkin

  3. Departments of Informatics, Plekhanov Russian University of Economics, Stremyanny Lane, 36, Moscow, Russia

    Sergey Yarushev

Authors
  1. Alexey Averkin
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  2. Sergey Yarushev
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Corresponding author

Correspondence to Sergey Yarushev .

Editor information

Editors and Affiliations

  1. Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    R. A. Aliev

  2. System Research Institute, Polish Academy of Sciences, Warsaw, Poland

    J. Kacprzyk

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    W. Pedrycz

  4. Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX, USA

    Mo. Jamshidi

  5. Azerbaijan State Oil and Industry University, Baku, Azerbaijan

    M. B. Babanli

  6. Department of Mechatronics, Near East University, Nicosia, Türkiye

    F. Sadikoglu

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Averkin, A., Yarushev, S. (2023). Fuzzy Approach to Explainable Artificial Intelligence. In: Aliev, R.A., Kacprzyk, J., Pedrycz, W., Jamshidi, M., Babanli, M.B., Sadikoglu, F. (eds) 15th International Conference on Applications of Fuzzy Systems, Soft Computing and Artificial Intelligence Tools – ICAFS-2022. ICAFS 2022. Lecture Notes in Networks and Systems, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-031-25252-5_27

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