An AI agent classifying contracts can loop due to several key factors. Often, it's caused by ambiguous or conflicting classification rules where contract features straddle multiple categories, making definitive assignment impossible. Insufficient or imbalanced training data also plays a significant role, as the agent lacks adequate examples for nuanced edge cases, leading to repeated classification attempts without resolution. Furthermore, a poorly defined stopping criterion or the absence of a maximum iteration limit within the agent's decision-making process can allow it to continuously re-evaluate without converging on a final label. Complex feedback loops within the system architecture, where the agent’s own uncertain outputs are used to re-initiate classification, can exacerbate this issue, preventing the agent from committing to a classification and resulting in an indefinite loop. More details: https://nesrepairsshop.com/Catalog/trigger.php?r_link=https://infoguide.com.ua/