.png){kind=icon}
返回
Managing complex adaptive systems: A resource/agent qualitative modelling perspective
.png){kind=icon}
OA
AI
DOI：10.1016/j.ejor.2020.08.007.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Complex adaptive systems are systems where those managing the system, the agents, interact with other competing agents and key resources available to the system. The behaviour of the agents and the resources are constantly changing over time thus resulting in complex systems of evolving problem configurations. Managing such a system can be very challenging, particularly when attempting to manage rather than simplify complexity. One particular problem is the need to take a comprehensive perspective of the complex system in order to manage it effectively. Resource structure and agent behaviour are interdependent and both interconnected components need to be considered in order to support optimal decision making. Due to the lack of an appropriate technique in the literature to achieve a comprehensive qualitative appreciation of resource/agent complex adaptive system behaviour, this paper describes the development of a novel qualitative modelling tool, a Resource/Agent Map, that aims to map and analyse both resources and agents interactive behaviour. We show how this modelling tool can help achieve a holistic appreciation of the resource/agent perspectives and generate scenario alternatives to inform policy decision making in respect to system management and regulation. A pharmaceutical example is used to demonstrate the modelling tool. (C) 2020 Published by Elsevier B.V.
Keyword:
Behavioural OR
Complex Adaptive Systems
System Dynamics
Agent based modelling
Problem Structuring Methods
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6
论文数:
2.2W
被引数:
6.4W
机构
引用论文
Modeling macroeconomies as open-ended dynamic systems of interacting agents.png)
AMERICAN ECONOMIC REVIEWOAAI
AMERICAN ECONOMIC REVIEWIF11.6
OAAI分享收藏Conceptualizing a Model: A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-2OAAI
OAAI分享收藏
查看更多内容