A modified Vicsek model based on the evolutionary game

Feng, You; Yang, Han-Xin; Li, Yumeng; Wei, Du; Wang, Gang

doi:10.1016/j.amc.2022.127565

Cited by 6 publications

(5 citation statements)

References 52 publications

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“…Providing more information Hierarchical society [24], Neighbors' degree [25] Weight difference [26], Direction preference [27] Adaptive velocity [28] Providing less information Evolutionary game theory [19], Line of sight [30] RVFVM [29], RNSVM [31] The proposed new neighbor strategy…”

Section: Category Methodsmentioning

confidence: 99%

“…Adjustments of the original VM realize the simulation of real creatures, such as bacterial colonies [16] and marching locusts [2]. More recent studies introduce response delay [17], obstacles [18], evolutionary game theory [19], and proportional-integral control strategy [20] to VM. In addition, phenomena including scale-free chaos [21] and multispecies flocking [22] were also studied.…”

Section: Introductionmentioning

confidence: 99%

“…Methods to accomplish improvements in the convergence performance of the original VM are another popular research branch, and this paper divides them into two categories. The first category realizes improvement by providing particles in VM with more information when updating their directions [24][25][26][27][28], and the second category is ultimately the opposite, providing less information [19,[29][30][31]. Examples of the first category include the adaptive velocity model proposed by Li Wei et al, where particles adjust their speed constantly according to additional consensus information provided [28].…”

Section: Introductionmentioning

confidence: 99%

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An Improved Vicsek Model of Swarms Based on a New Neighbor Strategy Considering View and Distance

Wang,

Zhao,

2023

Applied Sciences

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Collective behaviors in nature and human societies have been intensively studied in recent decades. The Vicsek model is one of the typical models that explain self-ordered particle systems well. In the original Vicsek model, the neighbor strategy takes all its neighbors’ mean directions into account when updating particles’ directions, which leads to a longer convergence time and higher computation cost due to the excess number of neighbors. In this paper, we introduce a new neighbor strategy to the Vicsek model. It defines that each particle will only select a certain number of particles with the farthest distance that fall into its vision sector as its neighbors. In addition, we classify the Vicsek model as the static model and the dynamic model according to whether the features of particles in the model are constant or not. Moreover, we design a new rule to apply the new neighbor strategy to dynamic Vicsek models. The simulation results indicate that our new neighbor strategy can significantly decrease the average number of particles’ neighbors but still be able to further enhance the Vicsek model’s convergence performance. The comparative results found that the static and dynamic model applied with the new neighbor strategy outperforms the models that only apply view restriction or remote neighbor strategy in noiseless and noisy conditions.

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Section: Category Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Vicsek Model of Swarms Based on a New Neighbor Strategy Considering View and Distance

Wang,

Zhao,

2023

Applied Sciences

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“…Further, the motion of biological entities is regulated by more complex internal processes such as protein expression regulation and information processing. Therefore, individual internal factors such as the sensitivity to stimuli, energy conversion efficiency and decision-making strategies all play crucial roles, [14][15][16][17][18] closely related to collective-state transitions in important biological processes such as embryonic development, wound healing and animal migration.…”

Section: Introductionmentioning

confidence: 99%

Disorder-to-order transition induced by spontaneous cooling regulation in robotic active matter

Hou 侯,

Wang 王,

Ma 马

et al. 2024

Chinese Phys. B

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In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustment. However, in active matter systems, the self-propulsion nature of active particles endows the systems with the ability to induce unique collective-state transitions by spontaneously regulating individual properties to alter the overall states. Based on an innovative robot-swarm experimental system, we demonstrate a field-driven active matter model capable of modulating individual motion behaviors through interaction with a recoverable environmental resource field by the resource perception and consumption. In the simulated model, by gradually reducing the individual resource-conversion coefficient over time, this robotic active matter can spontaneously decrease the overall level of motion, thereby actively achieving a regulation behavior like the cooling-down control. Through simulation calculations, we discover that the spatial structures of this robotic active matter convert from disorder to order during this process, with the resulting ordered structures exhibiting a high self-adaptability on the geometry of the environmental boundaries.

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“…In recent decades, the evolution of cooperation has been intensively studied under the framework of evolutionary game theory [1][2][3][4][5][6][7][8][9]. Abundant evolutionary game dynamics are considered in two-dimensional continuous planes [10][11][12][13][14][15][16][17]. In these works, the interaction radius is introduced to define the neighborhood of agents.…”

mentioning

confidence: 99%

Promotion of cooperation by payoff-based view radii in different interaction modes

Gao,

Han,

et al. 2024

EPL

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In this letter, we introduce the payoff-based view radii into evolutionary prisoner's dilemma games performed in a two-dimensional plane and study how the adaptive view radii affect cooperation. Two types of feedback are considered, positive feedback and negative one. In the case of positive feedback, high-payoff (low-payoff) agents have large (small) view radii. In the case of negative feedback, the things are opposite. Meanwhile, three different interaction modes are considered, one-way visual interaction, proactive visual interaction, and two-way visual interaction. Our results show that the payoff-based view radii could promote cooperation effectively in all cases. Especially, there exist optimal behaviors of cooperation for both positive feedback and negative feedback. When agents are allowed to move, we find that the cooperation level could be further improved by slow migration. Our results shed light on the promotion of cooperation by the adaptive view radii and suggest different ways to adjust view radii to achieve high cooperation levels in different interaction modes.

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A modified Vicsek model based on the evolutionary game

Cited by 6 publications

References 52 publications

An Improved Vicsek Model of Swarms Based on a New Neighbor Strategy Considering View and Distance

An Improved Vicsek Model of Swarms Based on a New Neighbor Strategy Considering View and Distance

Disorder-to-order transition induced by spontaneous cooling regulation in robotic active matter

Promotion of cooperation by payoff-based view radii in different interaction modes

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