Doctoral Dissertation Research: Heterogenous Preferences and Dynamics of Cooperation in Networked Public Goods Games: A Dialogue Between Experimental and Computational Approaches

博士论文研究：网络公共物品博弈中的异质偏好和合作动态：实验与计算方法之间的对话

• 批准号: 1324155
• 负责人: Ragan Petrie
• 金额: $ 2.16万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1324155&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Heterogenous; Preferences

A series of behavioral and computational experiments examine mechanisms by which cooperation is promoted in networked communities. Social groups are typically built around some form of network structure, and cooperation and efficiency within a group can be strongly affected by the flow of information determined by the structure of the network alone. Furthermore, experimental and observational studies show some real world groups are more successful at sustaining cooperation than others for a given network structure. This research explores the hypothesis that such heterogeneity is due to the interaction between the social preferences of individuals and the network structure that determines the dynamics of cooperation within a social group. Results from experimental economics have shown that there is a great deal of heterogeneity in terms of an individual?s preference to cooperate in group-dilemma settings. Depending on the composition of these cooperative types in the group, socially optimal cooperation may or may not be achieved without costly sanctions. This suggests that, in addition to the network structure, the distribution and the placement of different types within the network can also affect group outcomes. While it has been shown that network structure can facilitate cooperation, this proposal investigates the impact of the distribution of cooperative types and their placement within a given network structure on social outcomes.This project is an unusual use of both behavioral experiments and the computational simulation methodology known as agent-based modeling. This approach will allow us to systematically investigate the effects of network structure on cooperative behavior in a heterogeneous population. While observational data exists on naturally-occurring networks, the network structure and behavior of the individuals participating in the network have typically co-evolved. Thus, identification of the effect of structure on cooperation would be biased with this data because of individuals choosing the network in which to interact. The strength of this research is to use laboratory experiments to identify the cooperative preferences of individuals and then strategically place them in various network structures to examine how these types interact to enhance cooperation. The research can create counterfactuals of existing networks to examine how individuals with different levels of cooperative preferences would behave in a network they did not choose. The dialogue between the experiments and agent-based modeling will allow scholars to more efficiently investigate the network structures that have the potential to most enhance cooperation and to learn and calibrate the models to better represent behavior in social dilemmas.

一系列行为和计算实验检验了在网络社区中促进合作的机制。社会群体通常是围绕某种形式的网络结构建立的，群体内的合作和效率可能会受到仅由网络结构决定的信息流的强烈影响。此外，实验和观察研究表明，对于给定的网络结构，一些现实世界的团体比其他团体更成功地维持合作。本研究探索了这样一种假设，即这种异质性是由于个人的社会偏好和网络结构之间的相互作用，网络结构决定了社会群体内的合作动态。实验经济学的结果表明，在群体困境环境下，个体S倾向于合作，存在着很大的异质性。根据群体中这些合作类型的组成，在没有代价高昂的制裁的情况下，可能实现也可能不实现社会最佳合作。这表明，除了网络结构之外，网络中不同类型的分布和安置也会影响小组的结果。虽然已经证明网络结构可以促进合作，但该建议调查了合作类型的分布及其在给定网络结构中的位置对社会结果的影响。该项目是行为实验和基于代理的建模计算模拟方法的不同寻常的使用。这种方法将使我们能够系统地研究网络结构对异质种群中合作行为的影响。虽然观测数据存在于自然形成的网络上，但参与网络的个人的网络结构和行为通常是共同进化的。因此，由于个人选择在其中进行互动的网络，因此利用这些数据来确定结构对合作的影响将是有偏见的。这项研究的优势在于利用实验室实验来确定个体的合作偏好，然后战略性地将他们置于各种网络结构中，以考察这些类型是如何相互作用以加强合作的。这项研究可以创建现有网络的反事实，以检验具有不同合作偏好水平的个人在他们没有选择的网络中会如何表现。实验和基于代理的建模之间的对话将使学者能够更有效地研究具有最大潜力加强合作的网络结构，并学习和校准模型，以更好地代表社会困境中的行为。