4.7 Article

Non-Archimedean game theory: A numerical approach

期刊

APPLIED MATHEMATICS AND COMPUTATION
卷 409, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.amc.2020.125356

关键词

Game theory; Prisoner'S dilemma; Non-Archimedean quantities; Infinitesimal probability; Infinitesimal and infinite payoffs; Infinity computer; Grossone methodology

资金

  1. Italian Ministry of Education and Research (MIUR)
  2. University of Pisa [PRA_2018_81]

向作者/读者索取更多资源

This paper theoretically extends the Pure and Impure Prisoner's Dilemmas using the Grossone Methodology, and conducts numerical simulations using a Matlab simulator of the Infinity Computer. The effectiveness of the methodology is demonstrated in addressing complex problems and potentially performing computations in hardware, offering a new approach to model real-world scenarios.
In this paper we consider the Pure and Impure Prisoner's Dilemmas. Our purpose is to theoretically extend them when using non-Archimedean quantities and to work with them numerically, potentially on a computer. The recently introduced Sergeyev's Grossone Methodology proved to be effective in addressing our problem, because it is both a simple yet effective way to model non-Archimedean quantities and a framework which allows one to perform numerical computations between them. In addition, we could be able, in the future, to perform the same computations in hardware, resorting to the infinity computer patented by Sergeyev himself. After creating the theoretical model for Pure and Impure Prisoner's Dilemmas using Grossone Methodology, we have numerically reproduced the diagrams associated to our two new models, using a Matlab simulator of the Infinity Computer. Finally, we have proved some theoretical properties of the simulated diagrams. Our tool is thus ready to assist the modeler in all that problems for which a non-Archimedean Pure/Impure Prisoner's Dilemma model provides a good description of reality: energy market modeling, international trades modeling, political merging processes, etc. (C) 2020 Elsevier Inc. All rights reserved.

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