Mixed Strategies in Vector Optimization and Germeier’s Convolution
- 作者: Novikova N.1, Pospelova I.2
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隶属关系:
- Dorodnicyn Computing Center, Federal Research Center for Computer Science and Control, Russian Academy of Sciences
- Faculty of Computational Mathematics and Cybernetics, Moscow State University
- 期: 卷 58, 编号 4 (2019)
- 页面: 601-615
- 栏目: Systems Analysis and Operations Research
- URL: https://journals.rcsi.science/1064-2307/article/view/220434
- DOI: https://doi.org/10.1134/S1064230719040129
- ID: 220434
如何引用文章
详细
The simplest two-criteria examples of a vector optimization problem and a zero-sum game are considered to study the adequacy of using mixed strategies if the linear convolution is replaced by the Germeier’s convolution (the inverse logical convolution) for parametrizing the set of optimal solutions or values of the game and also for estimating the payoffs of all participants. It is shown that the linear convolution yields different results in a comparison with the averaged inverse logical convolution. The issues of stochastic vector optimization and various conceptual formalizations for the value of multi-criteria mixed strategies games are discussed.
作者简介
N. Novikova
Dorodnicyn Computing Center, Federal Research Center for Computer Science and Control,Russian Academy of Sciences
Email: ipospelova05@yandex.ru
俄罗斯联邦, Moscow, 119333
I. Pospelova
Faculty of Computational Mathematics and Cybernetics, Moscow State University
编辑信件的主要联系方式.
Email: ipospelova05@yandex.ru
俄罗斯联邦, Moscow, 119991
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