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knowledge-systems

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This theory redefines entropy as a constructive driving force that enables self-organizing structures in physical, informational, and abstract domains. It offers a novel view of dynamic equilibrium with applications in thermodynamics, AI, and knowledge systems. 本理論はエントロピーを「構成的な駆動因」として再定義し、物理・情報・抽象系における自己組織化を導きます。熱力学・AI・知識体系への応用可能性を示します。

  • Updated Jun 21, 2025

A constructive framework that systematically integrates causal structures across domains, enabling adaptive reasoning, predictive modeling, and cross-contextual understanding in AI and data systems. 構成的因果統合理論は、因果構造を領域横断的に統合し、AIやデータシステムにおける適応的推論・予測モデリング・文脈横断的理解を可能にする枠組みです。

  • Updated Jun 23, 2025

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