论文标题

通过先前承诺,成对和多玩家互动中协调的演变

Evolution of Coordination in Pairwise and Multi-player Interactions via Prior Commitments

论文作者

Bianca, Ogbo Ndidi, Elgarig, Aiman, Han, The Anh

论文摘要

开始集体努力后,重要的是要了解您的伴侣的偏好以及他们对共同目标的强烈承诺。就从事IT的后验福利和后果而建立先前的承诺或协议,这为确保合作提供了重要的机制。诉诸于进化游戏理论(EGT)的方法,我们在这里分析了如何在成对和多方互动中表现出不对称的回报结构时,如何将先前的承诺作为增强协调的工具。可以说,与合作相比,协调更为复杂,因为在协调问题中可能存在几个理想的集体结果(与相互合作相比,合作困境中唯一理想的集体结果)。我们的分析和通过数值模拟进行的分析表明,先前的承诺是否是增强协调的可行进化机制,而整体人口社会福利在很大程度上取决于竞争的集体利益和严重性,更重要的是,在承诺交易中如何解决不对称的益处。此外,在多方相互作用中,当需要高水平的群体多样性以进行最佳协调时,事先承诺被证明是至关重要的。结果对于不同的选择强度是可靠的。总体而言,我们的分析提供了对人类承诺能力驱动的行为进化的复杂性和美感的新见解,以及设计自治和分布式多机构系统以确保自主剂之间协调的设计。

Upon starting a collective endeavour, it is important to understand your partners' preferences and how strongly they commit to a common goal. Establishing a prior commitment or agreement in terms of posterior benefits and consequences from those engaging in it provides an important mechanism for securing cooperation. Resorting to methods from Evolutionary Game Theory (EGT), here we analyse how prior commitments can also be adopted as a tool for enhancing coordination when its outcomes exhibit an asymmetric payoff structure, in both pairwise and multiparty interactions. Arguably, coordination is more complex to achieve than cooperation since there might be several desirable collective outcomes in a coordination problem (compared to mutual cooperation, the only desirable collective outcome in cooperation dilemmas). Our analysis, both analytically and via numerical simulations, shows that whether prior commitment would be a viable evolutionary mechanism for enhancing coordination and the overall population social welfare strongly depends on the collective benefit and severity of competition, and more importantly, how asymmetric benefits are resolved in a commitment deal. Moreover, in multiparty interactions, prior commitments prove to be crucial when a high level of group diversity is required for optimal coordination. The results are robust for different selection intensities. Overall, our analysis provides new insights into the complexity and beauty of behavioral evolution driven by humans' capacity for commitment, as well as for the design of self-organised and distributed multi-agent systems for ensuring coordination among autonomous agents.

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