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ORIGINAL RESEARCH article

Front. Artif. Intell.

Sec. AI for Human Learning and Behavior Change

This article is part of the Research TopicAI Behavioral Science: Understanding, Modeling, and Aligning AI BehaviorsView all 3 articles

The Realism of Behavioral Theory-Based vs Non-Theory-Based Agents During a Simulated Infant Formula Shortage

Provisionally accepted
  • The MITRE Corporation, McLean, United States

The final, formatted version of the article will be published soon.

Abstract AI-driven digital twins and autonomous AI agents are increasingly used to simulate human behavior during crises. Incorporating behavioral science frameworks may improve agent realism, but this practice is still in its infancy. This research evaluates the realism of behavioral theory-based agents in a controlled experimental design. Using a simulated infant formula shortage in South Dallas County, we compare two conditions: one with theory-based agents, and another without. Participants (human raters) assessed the perceived realism of agent decisions across both conditions. Results showed significantly higher realism ratings for the theory-based agents, supporting our hypothesis. 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.

Keywords: agentic AI, AI Agent, AI Agent Validation, autonomous agents, Behavioral theory, Digital Twins

Received: 06 Oct 2025; Accepted: 13 Jan 2026.

Copyright: © 2026 Desens, Walling, O'Neill, Howard, Giammarino, Scannell, Wilkerson, Kemble, Nhial, Elson and Rosen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Linda Desens
Brandon Walling
Rhys O'Neill
Scott Rosen

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