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2021 | OriginalPaper | Buchkapitel

Unsupervised Barter Model Based on Natural Human Interaction

verfasst von : Yasmany Fernández-Fernández, Leandro L. Lorente-Leyva, Diego H. Peluffo-Ordóñez, Ridelio Miranda Pérez, Elia N. Cabrera Álvarez

Erschienen in: Recent Challenges in Intelligent Information and Database Systems

Verlag: Springer Singapore

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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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Titel: Unsupervised Barter Model Based on Natural Human Interaction
verfasst von: Yasmany Fernández-Fernández
Leandro L. Lorente-Leyva
Diego H. Peluffo-Ordóñez
Ridelio Miranda Pérez
Elia N. Cabrera Álvarez
Verlag: Springer Singapore
Buch: Recent Challenges in Intelligent Information and Database Systems
Print ISBN: 978-981-16-1684-6

Electronic ISBN: 978-981-16-1685-3

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-981-16-1685-3_32

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