エージェントベースのモデルで議論を捉える

Leon Assaad¹, Rafael Fuchs², Kirsty Phillips³

¹Munich Center for Mathematical Philosophy, LMU, Geschwister-Scholl-Platz 1, 80539 Munich, Bavaria Germany.

Topoi : an international review of philosophy

|August 20, 2025

まとめ

エージェントベースのモデル (ABM) は,議論を理由,シロジズム,および弁証法として区別することで複雑な議論をモデル化することができます. ベイジアンネットワークを使用するNormANフレームワークは,これらのモデルを比較し,議論の拡散を研究するための新しい方法を提供します.

科学分野:

コンピュータ社会科学
人工知能
認知科学

背景:

エージェントベースのモデル (ABM) は,複雑なシステムと新興特性を研究するために一般的です.
ABMの信念と意見の動態はオンラインのソーシャルメディアと科学的な議論に関連しています
現存するABMは,リッチな議論のシナリオを完全に捉えていません.

研究の目的:

エージェントベースの議論の枠組みを導入する.
議論の3つの概念を区別し分析する. 理由,シロジズム,そして弁証法.
議論モデルを比較し選択するための組織化スキームを提供する.

主な方法:

断言的な内容 (理由),前提と結論の関係 (シロジズム),会話的展開 (弁証法) として議論を区別する.
参照モデルとして,ベイジアンネットワーク上に ABM を構築する NormAN フレームワークを使用します.
議論の各概念をモデル化する複雑性の連続性を分析する.

主要な成果:

エージェントベースの議論モデルを比較し,選択するための新しい組織化スキーム.
議論の3つの概念がどのように相互に制約されているかを明確にします.
ノルマン・フレームワークは,議論の拡散に馴染みのある議論の側面と弁証法的な影響を捉えていることを示しています.

結論:

エージェントベースのモデルは,対話的側面を含む複雑な議論を効果的に表すことができます.
NormAN フレームワークは,議論の交換をモデル化するための汎用的なアプローチを提供します.
議論の拡散にどう影響するか更に研究が進められます

キーワード:

エージェントベースのモデリング議論ベイジアン認識論弁証法社会知識論

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