Modeling Tipping Point Theory Using Normative Multi-Agent Systems
Keywords
Networked agent societies; Norms; Tipping point theory
Abstract
Tipping points occur when a large number of group members radically modify their behaviors in response to small but significant events; after a critical point is reached, the behavior of the entire social system changes irrevocably. This paper proposes that normative multi-agent systems (NorMAS) can serve as excellent computational models for modeling and predicting tipping points. We illustrate how tipping point theory can be modeled with a standard social learning approach and replicate some of the key findings.
Publication Date
1-1-2015
Publication Title
Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume
3
Number of Pages
1731-1732
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84944705450 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84944705450
STARS Citation
Beheshti, Rahmatollah and Sukthankar, Gita, "Modeling Tipping Point Theory Using Normative Multi-Agent Systems" (2015). Scopus Export 2015-2019. 1841.
https://stars.library.ucf.edu/scopus2015/1841