Unverified50% confidenceFactExact time
LLM-based decision-making is non-deterministic—identical inputs may produce different execution paths due to the model's probabilistic sampling—and this is the fundamental technical reason why agents require human-machine collaboration protocols.
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8/22/2026
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Related Claims
UnverifiedLLM outputs are probabilistic—the same specification may produce drastically different behaviors across different runs—and therefore declarative specifications for AI Agents more closely resemble constraint declarations rather than state declarations.77% similarUnverifiedThe non-determinism of Agents stems from the token sampling mechanism of LLMs based on probability distributions, the dynamic changes in the context window, and silent updates to model versions.76% similarUnverifiedAlthough LLMs do not directly output normalized probability vectors, decision confidence can be approximately estimated through various engineering methods.76% similarUnverifiedLLM驱动的Agent引入了推理随机性（temperature参数控制采样）和上下文依赖性，使传统链路追踪工具无法直接捕获模型决策的语义信息74% similarUnverifiedLLM驱动的Agent行为由概率分布决定，使得经典MAS理论中的许多假设不再成立73% similar
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