The characteristics of average abundance function of multi-player threshold public goods evolutionary game model under redistribution mechanism

Based on a tripartite game model among suppliers of public goods, consumers, and the government, a tripartite repeated game model is constructed to analyze the evolution mechanism of which suppliers supply at low prices, consumers purchase, and the government provides incentives, and to establish the dynamics system of a repeated game. The equilibrium points of the evolutionary game are solved, and among them, the equilibrium points are found to satisfy the parameter conditions of ESS. The numerical simulation is employed to verify the impact of penalty coefficients and discount factors on the stability of strategies, which are adopted by the three players in a tripartite repeated game on public goods, and scenario analyses are conducted. The research results of this paper could provide a reference for the government, suppliers, and consumers to make rapid decisions, who are in the supply chain of public goods, especially quasi-public goods, such as coal, water, electricity, and gas, and help them to obtain stable incomes and then ensure the stable operation of the market.

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Cooperative Evolution Mechanism of Unmanned Swarm within the Framework of Public Goods Game

Mathematical Problems in Engineering ◽

10.1155/2021/5575815 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Minggang Yu ◽

Ming He ◽

Ziyu Ma ◽

Mingguang Zou ◽

Lei Wan ◽

...

Keyword(s):

Public Goods ◽

Evolutionary Game ◽

Centralized Control ◽

Public Goods Game ◽

Theoretical Derivation ◽

Evolution Mechanism ◽

Cooperative Evolution ◽

Average Abundance ◽

Actual Control

One of the key advantages of unmanned swarm operation is its autonomous cooperation. When the communication is interrupted or the centralized control manner is lost, the cooperative operation can still be carried out orderly. This work proposed a cooperative evolution mechanism within the framework of multiplayer public goods game to solve the problem of autonomous collaboration of unmanned swarm in case of failure of centralized control. It starts with the requirement analysis of autonomous cooperation in unmanned swarm, and then, the evolutionary game model of multiplayer public goods based on aspiration-driven dynamics is established. On this basis, the average abundance function is constructed by theoretical derivation, and furthermore, the influence of cost, multiplication factor, and aspiration level on the average abundance is simulated. Finally, the evolutionary mechanism of parameter adjustment in swarm cooperation is revealed via case study, and deliberate proposals are suggested to provide a meaningful exploration in the actual control of unmanned swarm cooperation.

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The characteristics of average abundance function with mutation of multi-player threshold public goods evolutionary game model under redistribution mechanism

BMC Ecology and Evolution ◽

10.1186/s12862-021-01847-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ke Xia

Keyword(s):

Evolutionary Game ◽

Approximate Expression ◽

Payoff Function ◽

Selection Intensity ◽

Expected Payoff ◽

Redistribution Mechanism ◽

Average Abundance ◽

And Function ◽

Approximate Expressions ◽

Different Levels

Abstract Background In recent years, the average abundance function has attracted much attention as it reflects the degree of cooperation in the population. Then it is significant to analyse how average abundance functions can be increased to promote the proliferation of cooperative behaviour. However, further theoretical analysis for average abundance function with mutation under redistribution mechanism is still lacking. Furthermore, the theoretical basis for the corresponding numerical simulation is not sufficiently understood. Results We have deduced the approximate expressions of average abundance function with mutation under redistribution mechanism on the basis of different levels of selection intensity $$\omega$$ ω (sufficiently small and large enough). In addition, we have analysed the influence of the size of group d, multiplication factor r, cost c, aspiration level $$\alpha$$ α on average abundance function from both quantitative and qualitative aspects. Conclusions (1) The approximate expression will become the linear equation related to selection intensity when $$\omega$$ ω is sufficiently small. (2) On one hand, approximation expression when $$\omega$$ ω is large enough is not available when r is small and m is large. On the other hand, this approximation expression will become more reliable when $$\omega$$ ω is larger. (3) On the basis of the expected payoff function $$\pi \left( \centerdot \right)$$ π ⋅ and function $$h(i,\omega )$$ h ( i , ω ) , the corresponding results for the effects of parameters (d,r,c,$$\alpha$$ α ) on average abundance function $$X_{A}(\omega )$$ X A ( ω ) have been explained.

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A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

Journal of Advanced Transportation ◽

10.1155/2019/8607942 ◽

2019 ◽

Vol 2019 ◽

pp. 1-17

Author(s):

Zhu Bai ◽

Mingxia Huang ◽

Shuai Bian ◽

Huandong Wu

Keyword(s):

Game Theory ◽

Evolutionary Game Theory ◽

Mode Choice ◽

Evolutionary Game ◽

Payoff Matrix ◽

Game Model ◽

Stable States ◽

Taxi Service ◽

Service Mode ◽

The Impact

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.

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Cooperation and competition between pair and multi-player social games in spatial populations

Scientific Reports ◽

10.1038/s41598-021-91532-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Attila Szolnoki ◽

Xiaojie Chen

Keyword(s):

Public Goods ◽

Evolutionary Game Theory ◽

Evolutionary Game ◽

Pair Interaction ◽

Public Goods Game ◽

Point Interactions ◽

Social Games ◽

The Public ◽

Specific Parameter ◽

Group Members

AbstractThe conflict between individual and collective interests is in the heart of every social dilemmas established by evolutionary game theory. We cannot avoid these conflicts but sometimes we may choose which interaction framework to use as a battlefield. For instance some people like to be part of a larger group while other persons prefer to interact in a more personalized, individual way. Both attitudes can be formulated via appropriately chosen traditional games. In particular, the prisoner’s dilemma game is based on pair interaction while the public goods game represents multi-point interactions of group members. To reveal the possible advantage of a certain attitude we extend these models by allowing players not simply to change their strategies but also let them to vary their attitudes for a higher individual income. We show that both attitudes could be the winner at a specific parameter value. Interestingly, however, the subtle interplay between different states may result in a counterintuitive evolutionary outcome where the increase of the multiplication factor of public goods game drives the population to a fully defector state. We point out that the accompanying pattern formation can only be understood via the multipoint or multi-player interactions of different microscopic states where the vicinity of a particular state may influence the relation of two other competitors.

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Evolutionary game analysis of information sharing by institutional investors

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219143 ◽

2021 ◽

pp. 1-9

Author(s):

Hua Li ◽

Qingqing Lou ◽

Qiubai Sun ◽

Bowen Li

Keyword(s):

Information Sharing ◽

Institutional Investors ◽

Information Exchange ◽

Evolutionary Game ◽

Stable State ◽

Point Of View ◽

Game Model ◽

Game Analysis ◽

Relationship Network ◽

The Relationship

In order to solve the conflict of interests of institutional investors, this paper uses evolutionary game model. From the point of view of information sharing, this paper discusses four different situations. Only when the sum of risk and cost is less than the penalty of free riding, the evolution of institutional investors will eventually incline to the stable state of information sharing. That is, the phenomenon of hugging. The research shows that the institutional investors are not independent of each other, but the relationship network of institutional investors for the purpose of information exchange. The content of this paper enriches the research on information sharing of institutional investors.

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