Cognitive Social Learners: An Architecture For Modeling Normative Behavior
Abstract
In many cases, creating long-term solutions to sustainability issues requires not only innovative technology, but also large-scale public adoption of the proposed solutions. Social simulations are a valuable but underutilized tool that can help public policy researchers understand when sustainable practices are likely to make the delicate transition from being an individual choice to becoming a social norm. In this paper, we introduce a new normative multi-agent architecture, Cognitive Social Learners (CSL), that models bottom-up norm emergence through a social learning mechanism, while using BDI (Belief/Desireflntention) reasoning to handle adoption and compliance. CSL preserves a greater sense of cognitive realism than influence propagation or infectious transmission approaches, enabling the modeling of complex beliefs and contradictory objectives within an agent-based simulation. In this paper, we demonstrate the use of CSL for modeling norm emergence of recycling practices and public participation in a smoke-free campus initiative.
Publication Date
6-1-2015
Publication Title
Proceedings of the National Conference on Artificial Intelligence
Volume
3
Number of Pages
2017-2023
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84959891394 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84959891394
STARS Citation
Beheshti, Rahmatollah; Ali, Awrad Mohammed; and Sukthankar, Gita, "Cognitive Social Learners: An Architecture For Modeling Normative Behavior" (2015). Scopus Export 2015-2019. 1855.
https://stars.library.ucf.edu/scopus2015/1855