A. V. Smirnov, A. V. Ponomarev, N. G. Shilov, T. V. Levashova
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Collaborative Decision Support Systems Based on Neuro-Symbolic Artificial Intelligence: Problems and Generalized Conceptual Model
Abstract
The development of artificial intelligence technologies and the growing complexity of decision-making when managing complex dynamic systems necessitate the joint work of humans and artificial intelligence, including as part of teams of heterogeneous participants (for example, experts and agents operating with artificial intelligence). The paper discusses the requirements for collaborative human-machine decision support systems and the problems that can arise during their creation. The methods of neuro-symbolic artificial intelligence can help resolve some of these problems. An analysis of modern results in the field of ontology-oriented neuro-symbolic artificial intelligence is carried out, primarily intended to explain neural network models using ontologies and 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.
期刊介绍：
Scientific and Technical Information Processing is a refereed journal that covers all aspects of management and use of information technology in libraries and archives, information centres, and the information industry in general. Emphasis is on practical applications of new technologies and techniques for information analysis and processing.
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