发表机构
Persagy Science and Technology Co.（珀萨吉科技有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究针对物理人工智能的冷启动死锁，提出人工物理世界的构成先验框架，确立合法性准则与分层下界，结合工业领域数据与可证伪预测展开论证，为机器智能攻克物理世界提供新路径。
AI 中文摘要
机器智能已攻克符号世界，但在物理世界停滞不前，这种停滞具有结构性：物理人工智能面临冷启动死锁——没有数据就没有智能，没有部署的智能就没有数据。本文的论点是：这种死锁是真实存在的，但分布不均，例外情况被称为人工物理世界。建筑物、工业设施和基础设施是被有意构建并记录的：设计好的人工制品附带可读档案，这些档案先于其实例存在并构成实例；在此处，规范是在实例之前颁布的，而非从实例中平均得出。本文有四项贡献：（一）从四世界本体论中推导构成先验框架的合法性准则：当且仅当对象领域被有意构建并留下可读档案时，先验提取才是合法的；该准则可通过适配方向进行检验——偏离构成规范是世界中的违规，而非模型的修订。（二）确立分层下界：任何此类框架至少有四个层次——语法、概念、知识、实例，因为四个构建目标会配对为相互不兼容的载体。（三）记录五个工业领域的部署主张及32类故障模式词汇表。（四）提出五个可证伪预测，核心预测可通过公共工程记录检验：若其不成立，则该框架不成立。半形式化论证（附录A）支持这些主张：无档案世界中规则覆盖的Gold型边界、封闭概念层上故障减少的可判定性结果，以及证书锚定演算的边界定理。大语言模型在此处占据重要地位——作为档案的读者，而非档案本身。这是三篇系列著作的第一篇，后续著作将探讨故意留下的未决问题。
英文摘要
Machine intelligence's push into the physical world is stuck on a gap: deployment demands auditable judgments from day one, fault samples are scarce or absent, and the norms defining "what counts as a fault" live in design documents, not in operational data. We argue this gap is structural, and locate where it can be legitimately closed. We divide the worlds machine intelligence faces into four (phenomenal, basic physical, artificial physical, artificial symbolic) along one axis of constraint strength, and give the Promulgation Criterion: extracting a prior framework from a world is legitimate if and only if the world is intentionally constituted (C1) and has left a readable generative archive (C2). On the criterion's two gradient axes, exactly one world is high on both: the artificial physical world (buildings, factories, infrastructure), whose norms precede their instances; the legitimate path is to extract the framework from the archive, not to induce it from data. We then show what shape such a framework must take: four construction goals force four incompatible carriers, hence at least four layers (syntax, concepts, knowledge, instances); on a closed concept layer fault localization is decidable in polynomial time, and every judgment is interrogable, traceable to a promulgated clause. The same criterion fixes the runtime division of labor with LLMs: promulgatable duties go to rule engines, on-site judgments beyond promulgation go to LLMs, and every generation sandwiched by promulgated clauses is auditable. The theory is falsifiable: four bets (P1-P4) with explicit falsification conditions -- among them that the next large-scale AI breakthrough occurs in the artificial physical world. Evidence: formal proofs (Appendix A); two cases (Appendix B: a cooling plant; the Curiosity rover Sol 1536 anomaly); eight reverse-read lineages, from BACnet to RDF/OWL (Appendix C).
CommentsMajor revision. Main paper (51 pp.) plus supplementary material (60 pp.): formal machinery, demonstrations, and witness dossiers moved to the supplement. New: LLM division-of-labor (Ch. 6); four predictions plus two structural corollaries (Ch. 7); I/O-logic semantics (A.1); non-identifiability boundary (A.2); sample-complexity separation (A.6); Curiosity Sol 1536 replay (B.2). Thesis unchanged
