当选择带来收益：具有广义交互模式的结构化公共物品博弈
When selection pays: structured public goods game with a generalized interaction mode
AI总结：
提出结构化公共物品博弈中个体仅选择部分邻居参与交互的模型，理论分析与数值计算证明该受限交互模式降低了合作主导背叛的临界增强因子，从而促进合作演化。
摘要：
公共物品博弈是研究结构化种群中合作演化的广泛使用范式。根据基本假设，交互图决定了参与者的连接，其中核心行动者与最近邻形成共同冒险。然而在现实中，并非所有伙伴都参与每场博弈。为详细阐述此观察，我们提出一个模型，个体仅从完整集合中选择部分被选邻居来组成公共物品群体。我们在弱选择极限下使用对近似方法探索潜在后果。我们理论分析了总邻居数和受限群体的实际规模如何影响合作主导背叛的临界增强因子。此外，我们系统地将模型与传统设置比较，表明当并非所有玩家都存在于社会困境中时，临界增强因子更低。因此，建议的受限交互模式为合作演化提供了更好条件。理论发现得到数值计算支持。
英文摘要：
The public goods game is a broadly used paradigm for studying the evolution of cooperation in structured populations. According to the basic assumption, the interaction graph determines the connections of a player where the focal actor forms a common venture with the nearest neighbors. In reality, however, not all of our partners are involved in every games. To elaborate this observation, we propose a model where individuals choose just some selected neighbors from the complete set to form a group for public goods. We explore the potential consequences by using a pair-approximation approach in a weak-selection limit. We theoretically analyze how the number of total neighbors and the actual size of the restricted group influence the critical enhancement factor where cooperation becomes dominant over defection. Furthermore, we systematically compare our model with the traditional setup and show that the critical enhancement factor is lower than in the case when all players are present in the social dilemma. Hence the suggested restricted interaction mode offers a better condition for the evolution of cooperation. Our theoretical findings are supported by numerical calculations.
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