School of Mathematical Science, Dalian University of Technology, Dalian 116024, China.
School of Physics, Dalian University of Technology, Dalian 116024, China.
Chaos. 2024 Jul 1;34(7). doi: 10.1063/5.0220267.
When players are dissatisfied with their actual payoffs, they will change the actuality by learning strategy of neighbors. The more effort players put in, the more likely they are to succeed in learning. Inspired by this, this paper proposes a two-stage strategy update rule based on learning cost. The players first decide whether to learn strategy according to the updating willingness. If the players imitate the strategy of neighbors, they need to pay the learning cost. Results show that for the well-mixed population, if the updating willingness is homogeneous and remains unchanged, reducing the updating willingness or increasing the learning cost can extend the life cycle of cooperators. If the updating willingness is heterogeneous and dynamically adjusted based on the difference between the actual payoff and the expected payoff, increasing aspiration value and learning cost promotes cooperation. For the structured population, if the updating willingness is homogeneous and remains unchanged, the moderate learning cost is beneficial for cooperators to resist the temptation of defection, and reducing updating willingness makes the system maintain cooperation within a larger parameter range. If the updating willingness is heterogeneous and dynamically adjusted, the larger learning cost and the appropriate aspiration value promote cooperation. This study highlights the complex dynamics of cooperation in paid strategy learning, contributing to the theory of cooperation in the evolutionary game.
当玩家对实际收益不满意时,他们会通过学习邻居的策略来改变现状。玩家付出的努力越多,成功学习的可能性就越大。受此启发,本文提出了一种基于学习成本的两阶段策略更新规则。玩家首先根据更新意愿决定是否学习策略。如果玩家模仿邻居的策略,他们需要支付学习成本。结果表明,对于完全混合的群体,如果更新意愿是同质的且保持不变,那么降低更新意愿或增加学习成本可以延长合作者的生命周期。如果更新意愿是异质的,并根据实际收益与预期收益之间的差异进行动态调整,那么增加愿望值和学习成本有助于促进合作。对于结构化群体,如果更新意愿是同质的且保持不变,那么适度的学习成本有利于合作者抵御背叛的诱惑,而降低更新意愿则使系统在更大的参数范围内维持合作。如果更新意愿是异质的并进行动态调整,那么较大的学习成本和适当的愿望值有助于促进合作。本研究强调了付费策略学习中合作的复杂动态,为进化博弈中的合作理论做出了贡献。