Model Validation of Agentic AI Systems: A POMDP-Based Framework for Belief-State, Forecast, and Policy Validation
Agentic artificial intelligence systems introduce a new class of model risk. Unlike traditional predictive models, autonomous agents continuously acquire information, form beliefs regarding latent states of the environment, generate forecasts, select actions, and adapt their behavior over time. Existing validation methodologies focus primarily on predictive accuracy and therefore provide limited insight into the quality of the underlying decision process. This paper proposes a model validation f
Record details
Published: 16 June 2026
Source: arXiv
Category: Research
Topics: Regulation · Agents & autonomy · Environment
Retrieved: 14 July 2026
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ethics.ai (16 June 2026), “Model Validation of Agentic AI Systems: A POMDP-Based Framework for Belief-State, Forecast, and Policy Validation,” evidence record 925, https://ethics.ai/record/925 (originally published by arXiv).
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