scholarly journals Evolutionary Game Theory: A Generalization of the ESS Definition

2019 ◽  
Vol 21 (04) ◽  
pp. 1950005
Author(s):  
Elvio Accinelli ◽  
Filipe Martins ◽  
Jorge Oviedo
Keyword(s):  
Game Theory ◽  
Strategic Planning ◽  
Evolutionary Game Theory ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Previous Literature ◽  
Evolutionarily Stable Strategies ◽  
Symmetric Games ◽  
Two Populations ◽  
Evolutionarily Stable

In this paper, we study the concept of Evolutionarily Stable Strategies (ESSs) for symmetric games with [Formula: see text] players. The main properties of these games and strategies are analyzed and several examples are provided. We relate the concept of ESS with previous literature and provide a proof of finiteness of ESS in the context of symmetric games with [Formula: see text] players. We show that unlike the case of [Formula: see text], when there are more than two populations an ESS does not have a uniform invasion barrier, or equivalently, it is not equivalent to the strategy performing better against all strategies in a neighborhood. We also construct the extended replicator dynamics for these games and we study an application to a model of strategic planning of investment.

scholarly journals The Impact of Penalty and Subsidy Mechanisms On The Decisions of Governments, Businesses, and Consumers During COVID-19 ——Tripartite Evolutionary Game Theory Analysis

2021 ◽  
Author(s):  
Yuxun Zhou ◽  
Rahman Mohammad Mafizur ◽  
Khanam Rasheda ◽  
Brad R. Taylor
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Virus Disease ◽  
Evolutionary Game ◽  
Initial Point ◽  
Evolutionarily Stable Strategies ◽  
Corona Virus ◽  
Evolutionary Stable Strategies ◽  
The Impact

Abstract Purpose – Based on the fact that punishment and subsidy mechanisms affect the anti-epidemic incentives of major participants in a society, the issue of this paper is how the penalty and subsidy mechanisms affect the decisions of governments, businesses, and consumers during Corona Virus Disease 2019. The goal of this paper is to understand strategic selections from governments, enterprises, and consumers to maximize their respective utility during Corona Virus Disease 2019, and the impact of penalty and subsidy mechanism on the decisions of governments, businesses, and consumers.Design/Methodology/approach - This paper proposes a tripartite evolutionary game theory, involving governments, businesses, and consumers, to firstly analyze the evolutionary stable strategies and to secondly analyze the impact of penalty and subsidy mechanism on their strategy selection during Corona Virus Disease 2019. Thirdly, this paper uses numerical analysis to simulate the strategy formation process of governments, enterprises, and consumers in Japan and India based on their different penalty and subsidy mechanism.Findings – This paper suggests that there are four evolutionarily stable strategies corresponding to the actual anti-epidemic situations of different countries in reality. We find that different subsidy and penalty mechanisms lead to different evolutionary stable strategies. If governments, enterprises, and consumers fighting the pandemic together, the government need to set a low subsidy mechanism and a high penalty mechanism.Originality/value - There are some limitations in the literature, such as long term strategies, rational hypothesis, and convergence path analysis in higher dimensional evolutionary game theory. This paper fills the gap and extends the theory of COVID-19 management theory. Firstly, this paper has important practical significance. This paper finds out the long-term equilibrium strategies of governments, businesses, and consumers under Corona Virus Disease 2019, which can provide an important theoretical and decision-making basis for pandemic prevention and control. Secondly, our paper extends the analytical paradigm of the tripartite evolutionary game theory. We extend the analysis of the dynamic process from the initial point to the convergence point and make a theoretical contribution to the development of high-dimensional evolutionary game theory.

Resource Allocation as an Evolving Strategy

1996 ◽  
Vol 4 (1) ◽  
pp. 33-55 ◽  
Author(s):  
Sverrir Olafsson
Keyword(s):  
Network Management ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Network Services ◽  
Efficient Utilization ◽  
Evolutionarily Stable Strategies ◽  
Network Utilization ◽  
Function Network ◽  
Evolutionarily Stable

The efficient utilization of resources is an issue of essential importance in modern network management. The emergence of increasingly complicated and continuously changing network services requires softer and fuzzier methods in network management. In this paper we demonstrate how evolutionary game theory can be used for an efficient allocation of service requirements onto an ensemble of heterogeneous network components. By incorporating differentiated pricing structures into a system utility function, network agents are encouraged to increase their usage of those components that are presently badly utilized. It is demonstrated how this approach can enhance network utilization significantly. Some new results regarding evolutionarily stable strategies in nonlinear evolutionary games are also reported.

scholarly journals Chris Cannings: A Life in Games

2019 ◽  
Vol 10 (3) ◽  
pp. 591-617
Author(s):  
D. Timothy Bishop ◽  
Mark Broom ◽  
Richard Southwell
Keyword(s):  
Evolutionary Game Theory ◽  
Segregation Analysis ◽  
Evolutionary Game ◽  
Multiplayer Games ◽  
Evolutionarily Stable Strategies ◽  
Matrix Games ◽  
War Of Attrition ◽  
Important Field ◽  
Evolutionarily Stable ◽  
John Maynard Smith

AbstractChris Cannings was one of the pioneers of evolutionary game theory. His early work was inspired by the formulations of John Maynard Smith, Geoff Parker and Geoff Price; Chris recognized the need for a strong mathematical foundation both to validate stated results and to give a basis for extensions of the models. He was responsible for fundamental results on matrix games, as well as much of the theory of the important war of attrition game, patterns of evolutionarily stable strategies, multiplayer games and games on networks. In this paper we describe his work, key insights and their influence on research by others in this increasingly important field. Chris made substantial contributions to other areas such as population genetics and segregation analysis, but it was to games that he always returned. This review is written by three of his students from different stages of his career.

scholarly journals On the replicator dynamics of lexical stress: accounting for stress-pattern diversity in terms of evolutionary game theory

Phonology ◽  
2017 ◽  
Vol 34 (3) ◽  
pp. 439-471 ◽  
Author(s):  
Andreas Baumann ◽  
Nikolaus Ritt
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Stress Pattern ◽  
Pattern Diversity ◽  
Word Forms ◽  
Final Stress ◽  
Polysyllabic Word ◽  
Stress Patterns

This paper accounts for stress-pattern diversity in languages such as English, where words that are otherwise equivalent in terms of phonotactic structure and morphosyntactic category can take both initial and final stress, as seen in ˈlentil–hoˈtel, ˈenvoy–deˈgree, ˈresearchN–reˈsearchNand ˈaccessV–acˈcessV. Addressing the problem in general and abstract terms, we identify systematic conditions under which stress-pattern diversity becomes stable. We hypothesise that words adopt stress patterns that produce, on average, the best possible phrase-level rhythm. We model this hypothesis in evolutionary game theory, predict that stress-pattern diversity among polysyllabic word forms depends on the frequency of monosyllables and demonstrate how that prediction is met both in Present-Day English and in its history.

scholarly journals Research on Optimization of Array Honeypot Defense Strategies Based on Evolutionary Game Theory

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 805
Author(s):  
Leyi Shi ◽  
Xiran Wang ◽  
Huiwen Hou
Keyword(s):  
Replicator Dynamics ◽  
Evolutionarily Stable Strategy ◽  
Evolutionary Game ◽  
Game Model ◽  
Evolutionarily Stable Strategies ◽  
Defense Strategies ◽  
Active Defense ◽  
Defense Technology ◽  
The Stability ◽  
Evolutionarily Stable

Honeypot has been regarded as an active defense technology that can deceive attackers by simulating real systems. However, honeypot is actually a static network trap with fixed disposition, which is easily identified by anti-honeypot technology. Thus, honeypot is a “passive” active defense technology. Dynamic honeypot makes up for the shortcomings of honeypot, which dynamically adjusts defense strategies with the attack of hackers. Therefore, the confrontation between defenders and attackers is a strategic game. This paper focuses on the non-cooperative evolutionary game mechanism of bounded rationality, aiming to improve the security of the array honeypot system through the evolutionarily stable strategies derived from the evolutionary game model. First, we construct a three-party evolutionary game model of array honeypot, which is composed of defenders, attackers and legitimate users. Secondly, we formally describe the strategies and revenues of players in the game, and build the three-party game payoff matrices. Then the evolutionarily stable strategy is obtained by analyzing the Replicator Dynamics of various parties. In addition, we discuss the equilibrium condition to get the influence of the number of servers N on the stability of strategy evolution. MATLAB and Gambit simulation experiment results show that deduced evolutionarily stable strategies are valid in resisting attackers.

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