This paper presents an agent-based model of team reasoning in a social dilemma game. Starting from the conundrum of empirically high levels of cooperation in dilemma games, contradicting traditional utility maximisation assumptions of game theory, Bacharach (1999, 2006) developed a theory of team reasoning. The idea behind team reasoning is that agents do not try to maximise their own utility but make choices as part of a team. This paper presents a model of preference convergence, mirroring adaptation dynamics of team reasoning. It describes an agent-based model simulating a repeated public goods game between a designated set of agents, a team. In the model agents have a probability to choose cooperation or defection, adjusting this preferences in the face of the revealed preferences of other players. The model is a classic binary choice model mapping an individual's preference for cooperation onto the binary behaviour choice of cooperation and defection. Preferences are updated in reaction to the behaviour choices of the team. Starting from simple stated preferences, the model implements a reframing of utility maximisation as applying to a group rather than an individual, modelling the importance of social interaction for individual preferences and the dependency of choice on social context. Results show that team reasoning, as implemented here, can explain high levels of cooperation found in the real world resulting from a wide range of settings. It also shows that team reasoning, as implemented here, is not a ‘sucker’ strategy except when adaptation rates are very slow. This paper demonstrates how agent-based models can be used to examine the role of social contexts for individual decision making.

本文提出了在社交困境游戏中基于智能体的团队推理模型。从两难博弈中经验丰富的高水平合作之谜出发，与传统的博弈论效用最大化假设相矛盾，Bacharach（1999，2006）发展了团队推理理论。。团队推理的思想是，代理人不试图最大化自己的效用，而是作为团队的一部分做出选择。本文提出了一种偏好收敛模型，该模型反映了团队推理的适应动态。它描述了一种基于代理的模型，用于模拟一组指定的代理，团队之间的重复公共物品博弈。在模型中，特工有可能选择合作或叛逃，面对其他参与者所揭示的偏好来调整这种偏好。该模型是经典的二元选择模型，将个人的合作偏好映射到合作和背叛的二元行为选择上。首选项会根据团队的行为选择进行更新。从简单的陈述偏好开始，该模型将效用最大化重新定义为应用于群体而非个人，对社交互动对于个人偏好以及选择对社会背景的依赖性的重要性进行建模。结果表明，如本文所述，团队推理可以解释因各种设置而在现实世界中发现的高水平合作。这也表明，除非适应率非常慢，否则在此实施的团队推理不是“吸盘”策略。本文演示了如何使用基于代理的模型来检查社会环境在个人决策中的作用。可以解释各种环境下在现实世界中发现的高水平合作。这也表明，除非适应率非常慢，否则在此实施的团队推理不是“吸盘”策略。本文演示了如何使用基于代理的模型来检查社会环境在个人决策中的作用。可以解释各种环境下在现实世界中发现的高水平合作。这也表明，除非适应率非常慢，否则在此实施的团队推理不是“吸盘”策略。本文演示了如何使用基于代理的模型来检查社会环境在个人决策中的作用。