Computer-Based Support for Searching Rational Strategies for Investors in Case of Insufficient Information on the Condition of the Counterparty

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Abstract

The paper considers the model of the procedure for mutual investment into information technology and systems, in the case when the financial resources of the counterparty of the investment belong to a fuzzy set. The model is intended for the decision support system that is being developed for investors, in cases that require a choosing of rational strategies. As an apparatus for solving the problem, we use the tools of the theory of multi-step games with several terminal surfaces. Such an approach, in our opinion, allows us to find solutions to the problem under consideration. A feature of the approach proposed in the paper, and accordingly the model, was the assumption that the one side or a player-investor, does not have complete information about the actions of the opposite side. Such incomplete information may include, for example, the lack of data on the financial strategies of the investment counterparty, on the status of its financial resources, etc. It is shown that the proposed model can become the basis for the corresponding algorithmic and software implementation during the development of an intelligent decision support system for choosing rational investor strategies. During computational experiments, we have evaluated the possibility of applying the model to such complex investment objects as information technology and systems. Investing in the latter, which include, for example, 5G technology; the Internet of things; SMARTCITY artificial intelligence; cybersecurity intelligent systems and others are associated with high risk and a high degree of uncertainty.

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Lakhno, V. A., Malikov, V. G., Kasatkin, D. Y., Blozva, A. I., Saiko, V. G., & Domrachev, V. N. (2020). Computer-Based Support for Searching Rational Strategies for Investors in Case of Insufficient Information on the Condition of the Counterparty. In Advances in Intelligent Systems and Computing (Vol. 1225 AISC, pp. 120–130). Springer. https://doi.org/10.1007/978-3-030-51971-1_10

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