The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules

Zhang, Mingzhen; Yang, Ning; Zhu, Xianglin; Wang, Yan

doi:10.1016/j.physa.2022.128220

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…In the above network evolutionary game (NEG) with the complexity indicated by 3 9 distinct initial action profiles, the dynamics of these profiles can be categorized into three types according to the principles outlined in Lemma 4 on system dynamics:…”

Section: Game Transformation and Algebraic Formulationmentioning

confidence: 99%

“…, 𝛿 17379 3 9 . These fixed points are stable states of the game where, once reached, the action profiles remain constant over time.…”

Section: Game Transformation and Algebraic Formulationmentioning

confidence: 99%

“…In [7], the effect of interaction networks on Nash equilibria in pairwise-interaction graphical games is explored. Besides, in [8,9], the authors studied the snowdrift game and public goods game on the scalefree networks, respectively. It should be pointed out that the above works verified their conclusions on the NEGs dynamics mainly by computer simulations.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and optimization of networked evolutionary game based on incomplete information with switched topologies

Gui,

Gao,

2024

IET Control Theory & Appl

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In the realm of evolutionary game theory, the majority of scenarios involve players with incomplete knowledge, specially regarding their opponents' actions and payoffs compounded by the ever‐shifting landscape of players' interactions. These dynamics present formidable challenges in both the analysis and optimization of game evolution. To address this, a novel model named the networked evolutionary game (NEG) is proposed based on incomplete information with switched topologies. This model captures situations where players possess limited insight into their opponents' benefits, yet make decisions based on their own payoffs while adapting to different networks and new players. To bridge the gap between incomplete and complete information games, R. Selten's transformation method is leveraged, a renowned approach that converts an incomplete information game into an interim agent game, thereby establishing the equivalence of pure Nash equilibria (NE) in both scenarios. Employing the semi‐tensor product (STP) of matrices, a powerful tool in logistic system, the evolution of the model is articulated through algebraic relationships. This enables to unravel the patterns of game evolution and identify the corresponding pure Nash equilibria. By introducing control players, strategically positioned within the game, optimized control is facilitated over the evolutionary trajectory, ultimately leading to convergence towards an optimal outcome. Finally, these concepts are illustrated with a practical example within the paper.

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Section: Game Transformation and Algebraic Formulationmentioning

confidence: 99%

“…, 𝛿 17379 3 9 . These fixed points are stable states of the game where, once reached, the action profiles remain constant over time.…”

Section: Game Transformation and Algebraic Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling and optimization of networked evolutionary game based on incomplete information with switched topologies

Gui,

Gao,

2024

IET Control Theory & Appl

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A novel profit allocation rule of complex product development networks under the position value

Zhang,

Yang,

Zhu

et al. 2024

RAIRO-Oper. Res.

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A fair and reasonable profit allocation mechanism is the key to ensuring the stability of complex product development networks. Considering the disconnectedness of development networks, this paper takes the Position value to allocate profits. Initially, this paper constructs the profit function of complex product development networks, which serves as the characteristic function in graph cooperative games. Subsequently, a real-world case is presented to demonstrate the profit allocation process using the Position value, allowing for an examination of the relationship between profits and firms' investments. Moreover, various factors are investigated to assess their influence on the profit allocation result, and a comparison is made between the Position value and the Myerson value. By adjusting the parameters and observing the numerical simulation, the research delves into the impact of key parameters on firms' profit allocation. The findings indicate that the network position and investment are directly proportional to firms' allocated profits. Additionally, the synergistic coefficient and benefit coefficient positively moderate firms' profits, while the cost coefficient of investment negatively moderates them. Notably, the Position value proves to be more suitable for complex product development networks than the Myerson value.

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Exploring the Impact of Group-Based Incentives on Cooperative Dynamics in Public Goods Game

Eddine Bahbouhi,

Islam Bouderba,

Elkouay

et al. 2024

2024 11th International Conference on Wireless Networks and Mobile Communications (WINCOM)

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The evolution of cooperation in public goods games on the scale-free community network under multiple strategy-updating rules

Cited by 4 publications

References 39 publications

Modeling and optimization of networked evolutionary game based on incomplete information with switched topologies

Modeling and optimization of networked evolutionary game based on incomplete information with switched topologies

A novel profit allocation rule of complex product development networks under the position value

Exploring the Impact of Group-Based Incentives on Cooperative Dynamics in Public Goods Game

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