Title

Agent Scheduling in Opinion Dynamics: A Taxonomy and Comparison Using Generalized Models

Document Type

Article

Publication Date

10-31-2019

Abstract

Opinion dynamics models are an important field of study within the agent-based modeling community. Agent scheduling elements within existing opinion dynamics models vary but are largely unjustified and only minimally explained. Furthermore, previous research on the impact of scheduling is scarce, partially due to a lack of a common taxonomy with which to discuss and compare schedules. The Synchrony, Actor type, Scale (SAS) taxonomy is presented, which aims to provide a common lexicon for agent scheduling in opinion dynamics models. This is demonstrated using a generalized repeated averaging model (GRAM) and a generalized bounded confidence model (GBCM). Significant differences in model outcomes with varied schedules are given, along with the results of intentional model biasing using only schedule variation. We call on opinion dynamics modelers to make explicit their choice of schedule and to justify that choice based on realistic social phenomena.
Abstract © JASSS.

Comments

The 'Link to Full Text' button on this record points to the freely-accessible article, hosted at the publisher website. The article is marked open access to read ("Green OA"). The publisher retains permissions to re-use and distribute this article. © JASSS 2019

DOI

10.18564/jasss.4065

Source Publication

Journal of Artificial Societies and Social Simulation : JASSS

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