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Two tales of complex system analysis: MaxEnt and agent-based modeling
The European Physical Journal Special Topics ( IF 2.8 ) Pub Date : 2020-07-07 , DOI: 10.1140/epjst/e2020-900137-x
Jangho Yang , Adrián Carro

Over the recent four decades, agent-based modeling and maximum entropy modeling have provided some of the most notable contributions applying concepts from complexity science to a broad range of problems in economics. In this paper, we argue that these two seemingly unrelated approaches can actually complement each other, providing a powerful conceptual/empirical tool for the analysis of complex economic problems. The maximum entropy approach is particularly well suited for an analytically rigorous study of the qualitative properties of systems in quasi-equilibrium. Agent-based modeling, unconstrained by either equilibrium or analytical tractability considerations, can provide a richer picture of the system under study by allowing for a wider choice of behavioral assumptions. In order to demonstrate the complementarity of these approaches, we use here two simple economic models based on maximum entropy principles – a quantal response social interaction model and a market feedback model –, for which we develop agent-based equivalent models. On the one hand, this allows us to highlight the potential of maximum entropy models for guiding the development of well-grounded, first-approximation agent-based models. On the other hand, we are also able to demonstrate the capabilities of agent-based models for tracking irreversible and out-of-equilibrium dynamics as well as for exploring the consequences of agent heterogeneity, thus fundamentally improving on the original maximum entropy model and potentially guiding its further extension.

中文翻译:

复杂系统分析的两个故事:MaxEnt和基于代理的建模

在最近的四十年中,基于主体的建模和最大熵建模为将复杂性科学的概念应用于经济学中的广泛问题提供了一些最引人注目的贡献。在本文中,我们认为这两种看似无关的方法实际上可以相互补充,为分析复杂的经济问题提供了强大的概念/经验工具。最大熵方法特别适合于对拟均衡系统的定性性质进行严格的分析研究。基于代理的建模不受平衡或分析性的考虑,可以通过允许更多的行为假设选择来提供正在研究的系统的更丰富的图片。为了证明这些方法的互补性,我们在此使用基于最大熵原理的两个简单经济模型-数量响应社会互动模型和市场反馈模型-为此,我们开发了基于代理的等效模型。一方面,这使我们能够突出最大熵模型的潜力,以指导发展良好的,基于第一近似代理的模型。另一方面,我们也能够证明基于代理的模型跟踪不可逆和失衡动力学以及探索代理异质性后果的能力,从而从根本上改进了原始的最大熵模型,并有可能指导其进一步扩展。为此,我们开发了基于代理的等效模型。一方面,这使我们能够突出最大熵模型的潜力,以指导发展良好的,基于第一近似代理的模型。另一方面,我们也能够证明基于代理的模型跟踪不可逆和失衡动力学以及探索代理异质性后果的能力,从而从根本上改进了原始的最大熵模型,并有可能指导其进一步扩展。为此,我们开发了基于代理的等效模型。一方面,这使我们能够突出最大熵模型的潜力,以指导发展良好的,基于第一近似代理的模型。另一方面,我们也能够证明基于代理的模型跟踪不可逆和不平衡动力学以及探索代理异质性后果的能力,从而从根本上改进了原始的最大熵模型,并有可能指导其进一步扩展。
更新日期:2020-07-07
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