Premium
Guiding the behavior of sociotechnical systems: The role of agent‐based modeling
Author(s) -
Heydari Babak,
Pennock Michael J.
Publication year - 2018
Publication title -
systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 50
eISSN - 1520-6858
pISSN - 1098-1241
DOI - 10.1002/sys.21435
Subject(s) - sociotechnical system , computer science , process (computing) , abstraction , corporate governance , knowledge management , relevance (law) , management science , domain (mathematical analysis) , process management , risk analysis (engineering) , engineering , business , political science , mathematical analysis , philosophy , mathematics , epistemology , finance , law , operating system
Abstract Performance and success for many sociotechnical systems depend on the way the social and the technical parts interact and coevolve with each other. Such dynamic interactions are increasingly becoming an essential part of design and governance of many emerging systems such as sharing economy platforms and critical infrastructures. This paper makes a case for an agent‐based approach to support the design and governance of sociotechnical systems and asserts that agent‐based modeling (ABM) and simulation, with certain suggested revisions, can be a powerful methodology in this domain. This paper addresses three goals: The first is to make a case for using ABM in the analysis, design, and governance of sociotechnical systems due to systemic trends that increase the relevance of ABM. The second goal is to point to a crucial difference between the application of ABM to natural, social, and physical systems, where most of the ABM literature resides and its application to sociotechnical systems. As a part of this goal, we will focus on using ABM as a design tool to guide the behavior of sociotechnical systems at higher levels of abstraction by changing parameters at lower levels. The third goal is to provide a perspective on the often controversial topic of model validation for ABM and discuss various levels of expectations and flavors of validation for ABM. To this end, and building on the framework proposed under the second goal, we present a process that we call quasi‐validation as a suggested high‐level framework to gain confidence in using agent‐based models for intervention‐based scenario studies. Finally, we discuss a set of future research directions in ABM for design and governance of sociotechnical systems.