Combining fuzzy cognitive maps with agent-based modeling: Frameworks and pitfalls of a powerful hybrid modeling approach to understand human-environment interactions
Combining fuzzy cognitive maps with agent-based modeling: Frameworks and pitfalls of a powerful hybrid modeling approach to understand human-environment interactions
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DOI：
10.1016/j.envsoft.2017.06.040
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发表时间：
2017-09-01
影响因子：
4.9
通讯作者：
Aminpour, Payam
中科院分区：
文献类型：
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作者：
Giabbanelli, Philippe J.;Gray, Steven A.;Aminpour, Payam
基于主体的建模（ABM）是一种成熟的技术，以捕捉社会生态系统中的人与环境的相互作用。作为一个微观模型，它明确地表示每个代理人，这样异构的决策过程（例如，基于利益相关者的信念和经验）可以预测聚合的个人行为的社会环境后果。与ABM相比，模糊认知映射从宏观角度看待世界，代表概念之间的因果联系，而不是单个实体。研究人员表示有兴趣调和两者，即采取混合方法，并利用每种方法的优势，更准确地模拟社会生态相互作用。直觉是采取FCM，它可以使用参与式建模工具快速开发，并使用它们来创建具有复杂决策过程的虚拟代理群体。在本文中，我们详细介绍了两种实现这种组合的方法，并强调了建模者需要注意的关键问题。(C)2017爱思唯尔有限公司版权所有
Agent-based modeling (ABM) is an established technique to capture human-environment interactions in socio-ecological systems. As a micro-model, it explicitly represents each agent, such that heterogeneous decision-making processes (e.g. based on the beliefs and experiences of stakeholders) can anticipate the socio-environmental consequences of aggregated individual behaviors. In contrast to ABM, Fuzzy Cognitive Mapping takes a macro-level view of the world that represents causal connections between concepts rather than individual entities. Researchers have expressed interest in reconciling the two, i.e. taking a hybrid approach and drawing of the strengths of each to more accurately model socio-ecological interactions. The intuition is to take FCMs, which can be quickly developed using participatory modeling tools and use them to create a virtual population of agents with sophisticated decision-making processes. In this paper, we detail two ways in which this combination can be done, and highlight the key questions that modelers need to be mindful of. (C) 2017 Elsevier Ltd. All rights reserved.