Abstract
Efficient collaboration of humans and machines has the great potential for improving many knowledge-intensive processes in variety of applications. Therefore, developing means supporting such collaboration and making it efficient is an important area of research. The paper presents a part of research aimed on the development of a collective intelligence environment that would support joint work of humans and machines on decision support problems, allowing participants to self-organize (define and adapt the plan of actions). In particular, it describes an approach to solving semantic interoperability issues in supporting human-machine collective intelligence for decision-making scenarios. The proposed approach is based on using multi-aspect ontologies and ontology-based smart spaces.
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The research is funded by Russian Science Foundation, project 19-11-00126.
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Smirnov, A., Ponomarev, A. (2021). Supporting Collective Intelligence of Human-Machine Teams in Decision-Making Scenarios. In: Russo, D., Ahram, T., Karwowski, W., Di Bucchianico, G., Taiar, R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, vol 1322. Springer, Cham. https://doi.org/10.1007/978-3-030-68017-6_115
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