Capraro Valerio, Perc Matjaž, Vilone Daniele
Department of Economics, Middlesex University, The Burroughs, London NW4 4BT, United Kingdom.
Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia.
Phys Rev E. 2020 Mar;101(3-1):032305. doi: 10.1103/PhysRevE.101.032305.
Lies can have a negating impact on governments, companies, and the society as a whole. Understanding the dynamics of lying is therefore of crucial importance across different fields of research. While lying has been studied before in well-mixed populations, it is a fact that real interactions are rarely well-mixed. Indeed, they are usually structured and thus best described by networks. Here we therefore use the Monte Carlo method to study the evolution of lying in the sender-receiver game in a one-parameter family of networks, systematically covering complete networks, small-world networks, and one-dimensional rings. We show that lies that benefit the sender at a cost to the receiver, the so-called black lies, are less likely to proliferate on networks than they do in well-mixed populations. Honesty is thus more likely to evolve, but only when the benefit for the sender is smaller than the cost for the receiver. Moreover, this effect is particularly strong in small-world networks, but less so in the one-dimensional ring. For lies that favor the receiver at a cost to the sender, the so-called altruistic white lies, we show that honesty is also more likely to evolve than it is in well-mixed populations. But contrary to black lies, this effect is more expressed in the one-dimensional ring, whereas in small-world networks it is present only when the cost to the sender is greater than the benefit for the receiver. Last, for lies that benefit both the sender and the receiver, the so-called Pareto white lies, we show that the network structure actually favors the evolution of lying, but this only occurs when the benefit for the sender is slightly greater than the benefit for the receiver. In this case again the small-world topology acts as an amplifier of the effect, while other network topologies fail to do the same. In addition to these main results we discuss several other findings, which together show clearly that the structure of interactions and the overall topology of the network critically determine the dynamics of lying.
谎言会对政府、公司乃至整个社会产生负面影响。因此，了解说谎的动态机制在不同研究领域都至关重要。虽然之前已经在充分混合的群体中对说谎进行过研究，但实际互动很少是充分混合的，这是事实。实际上，它们通常是结构化的，因此最好用网络来描述。所以在此我们使用蒙特卡罗方法，在一个单参数网络族中研究发送者 - 接收者博弈中说谎行为的演变，系统地涵盖完全网络、小世界网络和一维环。我们发现，以牺牲接收者为代价而使发送者受益的谎言，即所谓的恶意谎言，在网络中比在充分混合的群体中更不容易扩散。因此，诚实更有可能得以进化，但前提是发送者的收益小于接收者的成本。此外，这种效应在小世界网络中尤为显著，而在一维环中则较弱。对于以牺牲发送者为代价而使接收者受益的谎言，即所谓的利他善意谎言，我们发现诚实同样比在充分混合的群体中更有可能进化。但与恶意谎言相反，这种效应在一维环中表现得更为明显，而在小世界网络中，只有当发送者的成本大于接收者的收益时才会出现。最后，对于使发送者和接收者都受益的谎言，即所谓的帕累托善意谎言，我们发现网络结构实际上有利于说谎行为的进化，但这仅在发送者的收益略大于接收者的收益时才会发生。在这种情况下，小世界拓扑结构再次起到了放大效应的作用，而其他网络拓扑结构则没有这种效果。除了这些主要结果，我们还讨论了其他一些发现，这些发现共同清楚地表明，互动结构和网络的整体拓扑结构对说谎动态起着关键的决定性作用。
