ABSTRACT

Agent-based models present an ideal tool for interrogating the dynamics of communication and exchange. Such models allow individual aspects of human interaction to be isolated and controlled in a way that sheds new insight into complex behavioral phenomena. This approach is particularly valuable in settings beset by confounding factors and mixed empirical evidence. The political communication setting of deliberation is one such salient setting: in business, politics, and everyday life, individuals with varying opinions, experience, and information attempt to collaborate and make decisions. Empirical evidence suggests that such collaborative reasoning can lead to good decisions, yet there are numerous deliberative failures which may frequently cause groups to reach bad outcomes. Using the substantive setting of deliberation, this paper presents an agent-based model aimed at disambiguating the individual factors which influence decision-making conversations. We model this communicative process as a deliberative game of “giving and asking for reasons.” Agents share beliefs around possible policy initiatives and attempt to enact “good” policies through a process of mutual exchange and consideration. The model considers an interconnected policy landscape in which implementing or not implementing a policy mediates the value of other policies. Within this framework, the paper considers the impacts of three canonical failures of deliberation: limited cognitive capacity, group factions, and tendencies to make poor judgments when accepting or rejecting others’ views. We find that cognitive capacity can significantly decrease the ability of a group to reach a good decision. However, this effect appears to be mitigated for groups of opposing factions. Indeed, polarized groups do surprisingly well at identifying optimal policy solutions, suggesting that heterogeneous agents can achieve good outcomes if they are willing to talk and learn from each other.

摘要

基于代理的模型提供了一种理想的工具，用于询问通信和交换的动态。这样的模型允许人类交互的各个方面被隔离和控制，从而为复杂的行为现象提供新的洞察力。这种方法在受混杂因素和混合经验证据困扰的环境中特别有价值。商议的政治交流环境就是这样一种显着的环境：在商业、政治和日常生活中，具有不同意见、经验和信息的个人试图合作和做出决定。经验证据表明，这种协作推理可以导致良好的决策，但有许多商议失败可能经常导致团队达成糟糕的结果。利用审议的实质性设置，本文提出了一种基于代理的模型，旨在消除影响决策对话的个体因素的歧义。我们将这种交流过程建模为“给予和询问原因”的审议游戏。代理人围绕可能的政策举措分享信念，并试图通过相互交流和考虑的过程制定“好的”政策。该模型考虑了一个相互关联的政策格局，其中实施或不实施一项政策会影响其他政策的价值。在这个框架内，本文考虑了三种典型的审议失败的影响：有限的认知能力、群体派系以及在接受或拒绝他人观点时做出错误判断的倾向。我们发现认知能力会显着降低团队做出正确决定的能力。然而，对于敌对派系的团体，这种影响似乎得到了缓解。事实上，两极分化的群体在确定最佳政策解决方案方面做得非常好，这表明异质代理可以取得良好的结果如果他们愿意互相交谈和学习。