Cognitive social learners: An architecture for modeling normative behavior

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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.

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APA

Beheshti, R., Ali, A. M., & Sukthankar, G. (2015). Cognitive social learners: An architecture for modeling normative behavior. In Proceedings of the National Conference on Artificial Intelligence (Vol. 3, pp. 2017–2023). AI Access Foundation. https://doi.org/10.1609/aaai.v29i1.9441

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