提出统一框架，分析推理系统结构与失效模式。
Reasoning Systems as Structured Processes: Foundations, Failures, and Formal Criteria
- 将推理系统建模为包含解释空间与推理映射的结构化组合
- 定义一致性、合理性等内生标准，识别矛盾、不完整等典型失败
- 适合研究推理系统理论或故障诊断的学者
本文提出一个通用形式化框架，用于分析跨领域的推理系统架构。将推理系统建模为包含现象、解释空间、推理与生成映射及原则基础的结构化元组，兼容逻辑、算法和学习型推理过程，且不依赖特定算法或逻辑体系。框架涵盖一致性、合理性与完备性等基本内生标准，并归纳了矛盾、不完整、非收敛等典型失败模式。支持迭代优化与原则演化等动态行为。旨在建立可比较推理系统的理论基础，尤其适用于内部失效、适应或分裂等复杂情境。本文不提供具体架构方案，而是为未来在结构约束下的推理理论与实践研究提供支撑。
原文摘要 · Abstract (English)
This paper outlines a general formal framework for reasoning systems, intended to support future analysis of inference architectures across domains. We model reasoning systems as structured tuples comprising phenomena, explanation space, inference and generation maps, and a principle base. The formulation accommodates logical, algorithmic, and learning-based reasoning processes within a unified structural schema, while remaining agnostic to any specific reasoning algorithm or logic system. We survey basic internal criteria--including coherence, soundness, and completeness-and catalog typical failure modes such as contradiction, incompleteness, and non-convergence. The framework also admits dynamic behaviors like iterative refinement and principle evolution. The goal of this work is to establish a foundational structure for representing and comparing reasoning systems, particularly in contexts where internal failure, adaptation, or fragmentation may arise. No specific solution architecture is proposed; instead, we aim to support future theoretical and practical investigations into reasoning under structural constraint.
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