Abstract
The problem of improving the efficiency and quality of software development for AI systems, including knowledge bases, remains relevant. In this connection, a more complete inclusion of the end-users into the AI systems’ creating process with the transfer to them of separate programmers’ functions is promising. We have developed an original technique, namely PESoT (Prototyping Expert Systems based On Transformations), that is inspired by this idea and uses the following principles: visual programming, domain-specific languages, and model transformations for the purpose of automated generation of source codes and specifications. The paper describes its use for knowledge bases engineering in the case of aviation diagnostics, including main models, steps, and examples. The application of our technique required its extension in terms of supporting the formalism of event trees and their transformations. In particular, the algorithms and software (the Extended Event Tree Editor and the extension module for Personal Knowledge Base Designer, namely PKBD.ExTree) were developed. The developed software is used in the development of the “AviaTech Assistant” decision support system designed for technical personnel in troubleshooting during aviation diagnostics.
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Acknowledgment
The contribution of this work was supported by the Russian Science Foundation under Grant No. 22-21-00099.
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Yurin, A.Y., Nikolaychuk, O.A., Dorodnykh, N.O., Stolbov, A.B., Kotlov, Y.V., Popov, V.M. (2023). Knowledge Bases Engineering Based on Event Trees Transformations: A Case Study for Aircraft Diagnostics. In: Kovalev, S., Sukhanov, A., Akperov, I., Ozdemir, S. (eds) Proceedings of the Sixth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’22). IITI 2022. Lecture Notes in Networks and Systems, vol 566. Springer, Cham. https://doi.org/10.1007/978-3-031-19620-1_1
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