@article{Beheshti_Mohammed Ali_Sukthankar_2015, title={Cognitive Social Learners: An Architecture for Modeling Normative Behavior}, volume={29}, url={https://ojs.aaai.org/index.php/AAAI/article/view/9441}, DOI={10.1609/aaai.v29i1.9441}, abstractNote={ <p> 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/Desire/Intention) 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. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Beheshti, Rahmatollah and Mohammed Ali, Awrad and Sukthankar, Gita}, year={2015}, month={Feb.} }