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Recent Advances in Game and Decision Theory: Structures, Models, Applications...
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Recent Advances in Game and Decision Theory: Structures, Models, Applications and Software Implementation 2019

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 16427

Special Issue Editor

Prof. Dr. David Carfì

E-Mail Website
Guest Editor
Department of Mathematics, University of California Riverside, Riverside, CA 92521, USA
Interests: mathematical economics; game theory; decision theory; risk management; bargaining theory; finance; econophysics; quantum finance; foundations of quantum mechanics; relativistic quantum mechanics; Schwartz distribution theory; differential manifolds; relativity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are renewing the Special Issue titled "Recent Advances in Game and Decision Theory: Structures, Models, Applications and Software Implementation" in the MDPI journal Mathematics.

For this renewal, we want to collect research and survey papers about game theory and decision theory, from the wide domains of these two fields. In particular, papers devoted to significant applications in economics, finance, industrial organization, and other concrete fields are welcomed, as well as papers in which the research requires software implementations, automatic numerical calculus, and renowned software such as Matlab, Mathematica, and so on.

Game theory revealed a major method used in mathematical economics and business administration for modeling competing behaviors of interacting agents. We welcome applications in a wide range of economic phenomena and related approaches, such as auctions, bargaining, mergers and acquisitions, co-opetition, pricing, fair division, duopolies, oligopolies, social network formation, agent-based computational economics, general equilibrium, mechanism design, voting systems, experimental economics, behavioral economics, information economics, industrial organization, political economy, global bargaining scenarios, climate change bargaining scenarios, global feeding decision problems, and so on.

Papers highlighting interrelations among different approaches to the above themes, with particular emphasis on econophysics, quantum mechanics, and statistical physics approaches, are equally welcomed.

Prof. Dr. David Carfì
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Game theory
  • Decision theory
  • Risk theory 
  • Evolutionary games
  • Bayesian games
  • Decisions in finance
  • Microeconomics and macroeconomics games
  • Political economics and decisions
  • Econo-physics and games
  • Statistical economics
  • Potential games
  • Quantum games
  • Global bargaining scenarios 
  • Climate change decision problems 

Published Papers (3 papers)

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Research

20 pages, 912 KiB  
Article
A Machine Learning Approach to Forecast Economic Recessions—An Italian Case Study
by Giovanni Cicceri, Giuseppe Inserra and Michele Limosani
Mathematics 2020, 8(2), 241; https://doi.org/10.3390/math8020241 - 13 Feb 2020
Cited by 21 | Viewed by 12141
Abstract
In economic activity, recessions represent a period of failure in Gross Domestic Product (GDP) and usually are presented as episodic and non-linear. For this reason, they are difficult to predict and appear as one of the main problems in macroeconomics forecasts. A classic [...] Read more.
In economic activity, recessions represent a period of failure in Gross Domestic Product (GDP) and usually are presented as episodic and non-linear. For this reason, they are difficult to predict and appear as one of the main problems in macroeconomics forecasts. A classic example turns out to be the great recession that occurred between 2008 and 2009 that was not predicted. In this paper, the goal is to give a different, although complementary, approach concerning the classical econometric techniques, and to show how Machine Learning (ML) techniques may improve short-term forecasting accuracy. As a case study, we use Italian data on GDP and a few related variables. In particular, we evaluate the goodness of fit of the forecasting proposed model in a case study of the Italian GDP. The algorithm is trained on Italian macroeconomic variables over the period 1995:Q1-2019:Q2. We also compare the results using the same dataset through Classic Linear Regression Model. As a result, both statistical and ML approaches are able to predict economic downturns but higher accuracy is obtained using Nonlinear Autoregressive with exogenous variables (NARX) model. Full article
(This article belongs to the Special Issue Recent Advances in Game and Decision Theory: Structures, Models, Applications and Software Implementation 2019)
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23 pages, 1437 KiB  
Article
The Trapezoidal Fuzzy Two-Dimensional Linguistic Power Generalized Hamy Mean Operator and Its Application in Multi-Attribute Decision-Making
by Yisheng Liu and Ye Li
Mathematics 2020, 8(1), 122; https://doi.org/10.3390/math8010122 - 13 Jan 2020
Cited by 6 | Viewed by 1866
Abstract
As a common information aggregation tool, the Hamy mean (HM) operator can consider the relationships among multiple input elements, but cannot adjust the effect of elements. In this paper, we integrate the idea of generalized a weighted average (GWA) operator into the HM [...] Read more.
As a common information aggregation tool, the Hamy mean (HM) operator can consider the relationships among multiple input elements, but cannot adjust the effect of elements. In this paper, we integrate the idea of generalized a weighted average (GWA) operator into the HM operator, and reduce the influence of related elements by adjusting the value of the parameter. In addition, considering that extreme input data may lead to a deviation in the results, we further combine the power average (PA) operator with HM, and propose the power generalized Hamy mean (PGHM) operator. Then, we extend the PGHM operator to the trapezoidal fuzzy two-dimensional linguistic environment, and propose two new information aggregation tools, the trapezoidal fuzzy two-dimensional linguistic power generalized Hamy mean (TF2DLPGHM) operator and the weighted TF2DLPGHM (WTF2DLPGHM) operator. Some properties and special cases of these operators are discussed. Furthermore, based on the proposed WTF2DLPGHM operator, a new multi-attribute decision-making method is proposed for lean management evaluation of industrial residential projects. Finally, an example is given to show the specific steps, effectiveness, and superiority of the method. Full article
(This article belongs to the Special Issue Recent Advances in Game and Decision Theory: Structures, Models, Applications and Software Implementation 2019)
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26 pages, 317 KiB  
Article
Models for MADM with Single-Valued Neutrosophic 2-Tuple Linguistic Muirhead Mean Operators
by Jie Wang, Jianping Lu, Guiwu Wei, Rui Lin and Cun Wei
Mathematics 2019, 7(5), 442; https://doi.org/10.3390/math7050442 - 17 May 2019
Cited by 35 | Viewed by 1948
Abstract
In this article, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with single-valued neutrosophic 2-tuple linguistic numbers (SVN2TLNs) to propose the single-valued neutrosophic 2-tuple linguistic Muirhead mean (SVN2TLMM) operator, the single-valued neutrosophic 2-tuple linguistic weighted Muirhead mean (SVN2TLWMM) [...] Read more.
In this article, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with single-valued neutrosophic 2-tuple linguistic numbers (SVN2TLNs) to propose the single-valued neutrosophic 2-tuple linguistic Muirhead mean (SVN2TLMM) operator, the single-valued neutrosophic 2-tuple linguistic weighted Muirhead mean (SVN2TLWMM) operator, the single-valued neutrosophic 2-tuple linguistic dual Muirhead mean (SVN2TLDMM) operator, and the single-valued neutrosophic 2-tuple linguistic weighted dual Muirhead mean (SVN2TLWDMM) operator. Multiple attribute decision making (MADM) methods are then proposed using these operators. Finally, we utilize an applicable example for green supplier selection in green supply chain management to prove the proposed methods. Full article
(This article belongs to the Special Issue Recent Advances in Game and Decision Theory: Structures, Models, Applications and Software Implementation 2019)
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