cs.AI updates on arXiv.org 07月21日 12:06
From Extraction to Synthesis: Entangled Heuristics for Agent-Augmented Strategic Reasoning
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本文提出一种结合启发式提取、语义激活和组合合成的新型混合架构,用于增强型战略推理。通过量子认知研究启发,模型融合冲突启发式,生成情境敏感叙述,并通过案例研究验证。

arXiv:2507.13768v1 Announce Type: new Abstract: We present a hybrid architecture for agent-augmented strategic reasoning, combining heuristic extraction, semantic activation, and compositional synthesis. Drawing on sources ranging from classical military theory to contemporary corporate strategy, our model activates and composes multiple heuristics through a process of semantic interdependence inspired by research in quantum cognition. Unlike traditional decision engines that select the best rule, our system fuses conflicting heuristics into coherent and context-sensitive narratives, guided by semantic interaction modeling and rhetorical framing. We demonstrate the framework via a Meta vs. FTC case study, with preliminary validation through semantic metrics. Limitations and extensions (e.g., dynamic interference tuning) are discussed.

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混合架构 战略推理 启发式 语义激活
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