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Individual behavior and macro social properties. An agent based model

机译:个人行为和宏观社会属性。基于代理的模型

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摘要

The paper aims at presenting an agent-based modeling exercise to illustrate how small differences in the cognitive properties of agents can generate very different macro social properties. We argue that it is not necessary to assume highly complicated cognitive architectures to introduce cognitive properties that matter for computational social science purposes. Our model is based on different simulation settings characterized by a gradual sophistication of behavior of agents, from simple heuristics to macro-micro feedback and other second-order properties. Agents are localized in a spatial interaction context. They have an individual task but are influenced by a collective coordination problem. The simulation results show that agents can generate efficiency at a macro level particularly when socio-cognitive sophistication of their behavior increases
机译:本文旨在提出一种基于主体的建模练习,以说明主体的认知特性上的微小差异如何产生非常不同的宏观社会特性。我们认为没有必要假设高度复杂的认知体系结构来引入对计算社会科学目的至关重要的认知属性。我们的模型基于不同的仿真设置,其特征是代理行为的逐渐复杂化,从简单的启发式方法到宏微反馈和其他二阶属性。代理位于空间交互上下文中。他们有单独的任务,但受到集体协调问题的影响。仿真结果表明,代理可以在宏观水平上产生效率,尤其是当他们的行为的社会认知水平提高时

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