Abstract The evolution of network cooperation has become a hot topic in recent years. When players participate in a network game, they gain payoffs by playing games with their neighbors according to their different choices. Besides the network game itself, we focus on two interesting human behaviors: transcendental behavior and disturbance behavior. The former means some players choose a different strategy if they recognize global information and not just local information, and the latter describes the benchmark effect from all populations. To explore our proposed mechanisms, we introduce new transfer rules: the amendatory Fermi rule and transcendental probability, in the framework of memory-based donor and recipient game and observe their final cooperation rates and payoff distribution. The results from human experiments and simulations show that the introduction of new mechanisms will lead higher cooperation rates, which in turn will lead to a balanced payoff distribution. Finally, we observe that a fair society dominated by cooperative behavior will undoubtedly promote the development of human society.

中文翻译：

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先验行为和干扰行为有利于人类发展

摘要 网络协作的演进成为近年来的热门话题。当玩家参与网络游戏时，他们根据自己的不同选择，通过与邻居玩游戏来获得收益。除了网络游戏本身，我们关注两种有趣的人类行为：先验行为和干扰行为。前者意味着一些参与者在识别全局信息而不仅仅是局部信息时会选择不同的策略，后者描述了来自所有人群的基准效应。为了探索我们提出的机制，我们在基于记忆的捐赠者和接受者博弈的框架内引入了新的转移规则：修正费米规则和先验概率，并观察他们最终的合作率和收益分布。人体实验和模拟结果表明，新机制的引入会带来更高的合作率，进而导致收益分配均衡。最后，我们观察到，一个以合作行为为主的公平社会，无疑会促进人类社会的发展。