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Updated: Jul 12, 2026

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
マルチエージェントシステムにおける社会的採用をモデル化するための熱力学的枠組み
Guilherme S Y Giardini1, Carlo R daCunha1
1Northern Arizona University, Sanghi College of Engineering (SCE), Flagstaff, Arizona 86011, USA and School of Informatics, Computing, and Cyber Systems (SICCS), Flagstaff, Arizona 86011, USA.
Physical review. E
|February 20, 2026
まとめ
私たちは,イノベーションの採用と放棄をモデル化するための熱力学的フレームワークを導入します. このアプローチは,統計力学を用いて社会技術的なシステムの複雑な動態を説明し,ハイブリッドの熱力学-統計的サインを明らかにします.
科学分野:
- 熱力学は熱力学である.
- 統計力学 統計力学 統計力学
- 社会技術システム分析 社会技術システム分析
背景:
- イノベーションの採用と放棄は,複雑なダイナミクスを示しています.
- 既存のモデルでは,社会技術系における新興行動が完全に捉えられないかもしれません.
- これらのダイナミクスを理解するためには,統一された枠組みが必要である.
研究 の 目的:
- イノベーションの採用と放棄をモデリングするための熱力学的枠組みを開発する.
- これらのダイナミクスを分析するために統計力学を利用する.
- 社会技術系における新興行動をとるため.
主な方法:
- 統計力学に基づく熱力学フレームワークを開発した.
- 経験的な採用分布モデルからカノンアンサンブルを構築した.
- 効果的なポテンシャルを定義し,動的ラグランジアン式を導いた.
- フィールド理論を用いて,発生する行動を分析した.
主要な成果:
- このフレームワークは,ゴムペルツ型とマクスウェル・ボルツマン型の均衡分布を生成します.
- 派生フィールド理論は,イノベーションダイナミクス (抑制,ピーク,減少) の重要な特徴を捉えています.
- 効果的な温度,エントロピー,および均衡点が解釈されました.
結論:
- 熱力学的枠組みは,イノベーションの採用と放棄のダイナミクスを成功裏にモデル化しています.
- 社会技術的システムは,ハイブリッドの熱力学-統計的サインを示します.
- このアプローチは,複雑なシステムにおける新興行動に関する新しい洞察を提供します.
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