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Decision support systems
Neuro-symbolic artificial intelligence in collaborative decision support systems
A. V. Smirnov, A. V. Ponomarev, N. G. Shilov, T. V. Levashova St. Petersburg Federal Research Center
of the Russian Academy of Sciences, St. Petersburg, Russia
Abstract:
The paper discusses the requirements for collaborative human-machine decision support systems and the problems that arise during their creation. The methods of neuro-symbolic artificial intelligence can help to resolve some of these problems. The analysis of modern results in the field of ontology-oriented neuro-symbolic artificial intelligence is carried out, primarily aimed at explaining neural network models using ontologies and using symbolic knowledge to improve the efficiency of neural network models. A conceptual model of a collaborative human-machine decision support system based on ontology-oriented neuro-symbolic intelligence is proposed.
Keywords:
decision support systems, neuro-symbolic intelligence, collaborative systems.
Citation:
A. V. Smirnov, A. V. Ponomarev, N. G. Shilov, T. V. Levashova, “Neuro-symbolic artificial intelligence in collaborative decision support systems”, Artificial Intelligence and Decision Making, 2022, no. 3, 36–50; Scientific and Technical Information Processing, 50:6 (2023), 635–645
Linking options:
https://www.mathnet.ru/eng/iipr69 https://www.mathnet.ru/eng/iipr/y2022/i3/p36
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Statistics & downloads: |
Abstract page: | 17 | Full-text PDF : | 29 |
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