Temporal Grounding in Agentic Systems: Overcoming the Infinite Loop Problem

ABSTRACT

One of the most persistent failure modes in autonomous Agentic AI is the 'Infinite Loop'—where an agent becomes stuck continuously re-executing a failed API call or repeating a flawed logical deduction. We introduce Temporal Grounding, a novel cognitive framework that grants agents an internal sense of computational time and execution history. By implementing a 'Frustration Metric' that scales non-linearly with repeated state visits, the agent is forced to autonomously break out of loops, escalate the issue to a human supervisor, or abandon the sub-task entirely. Empirical results show a 91% reduction in stalled executions in open-ended web navigation tasks.