The realism of behavioral theory-based vs. non-theory-based AI agents during a simulated infant formula shortage
This study constitutes an early effort to assess behavioral theory in simulation frameworks and establish a repeatable method for assessing behavioral fidelity. It provides policymakers and researchers with a theory-informed approach for enhancing AI agent realism, with the goal of increasing trust in digital twin models used for decision support in high-stakes environments.
Authors
- Brandon M. Walling (ORCID: https://orcid.org/0000-0002-7714-7380)
- Scott L. Rosen
- Taylor H. Wilkerson
- Sara Beth Elson
- Mary Giammarino (ORCID: https://orcid.org/0000-0003-0306-9559)
- Denise Scannell
- Linda Desens (ORCID: https://orcid.org/0000-0002-3108-4310)
- Vanessa Howard
- Rhys O’Neill
- Nyalok Nhial
- Anya Kemble
Institutions
- Mitre (United States) (US)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2026-02-09
- DOI
- https://doi.org/10.3389/frai.2026.1719703
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00