Abstract
Human interaction is a natural process in business management. In various indigenous cultures, the natives still use a barter system to reach consensus or balances that determine the essence of their economies. The present investigation consists of the presentation of an unsupervised model based on pure barter. The main contribution sought is to visualize the balance that is achieved in an unsupervised environment of two entities that are close to reaching an agreement. Both Game Theory and Walrasian Theory deal with the problem of exchange of goods. However, the current objective is to show the barter model from its simplest bases for the construction of an unsupervised automatic learning scheme where a system of pairs of agents represent a basic model for decision making when guaranteeing an agreement.
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Acknowledgment
The authors are greatly grateful by the support given by the SDAS Research Group (www.sdas-group.com). As well, acknowledge to the project "Development of new mathematical models and methods for decision making" of the Department of Mathematics and Computation of the University of Havana.
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Fernández-Fernández, Y., Lorente-Leyva, L.L., Peluffo-Ordóñez, D.H., Pérez, R.M., Álvarez, E.N.C. (2021). Unsupervised Barter Model Based on Natural Human Interaction. In: Hong, TP., Wojtkiewicz, K., Chawuthai, R., Sitek, P. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2021. Communications in Computer and Information Science, vol 1371. Springer, Singapore. https://doi.org/10.1007/978-981-16-1685-3_32
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