Beyond Component Testing: Validating Agentic AI Systems
Agentic AI systems act through multi-step trajectories that combine planning, tool use, memory, interaction, and adaptation. This behavior stretches validation practice beyond component testing and one-shot input--output evaluation, because acceptable system behavior now depends on how decisions unfold over time and under changing environmental conditions. This survey synthesizes 257 papers spanning agent evaluation, software assurance, cyber-physical systems, runtime monitoring, and regulatory
Record details
Published: 31 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Regulation · Military & security · Agents & autonomy · Environment
Retrieved: 3 August 2026
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How to cite this record
ethics.ai (31 July 2026), “Beyond Component Testing: Validating Agentic AI Systems,” evidence record 15768, https://ethics.ai/record/15768 (originally published by arXiv cs.AI).
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