用范畴数学建模智能体的主观体验，为人工意识提供新框架
Categorical AI phenomenology: A first-person approach
- 以第一人称视角重构意识，用Q网络构建动作与体验的数学关系
- 将智能体与世界交互视为动态过程，体现经验的主动、嵌入与延伸特性
- 适合研究意识理论、具身智能与计算哲学的学者参考
本文提出一种以现象学为导向的人工意识研究方法，将意识重新定义为智能体通过其与世界交互界面所展开的主观体验。方法论重心转向第一人称结构，利用源自Q网络的范畴数学模型来捕捉行为与现象学不变量之间的关系。在此框架中，Q网络被视为编码智能体-世界互动的关联接口，类似于计算机的动态状态依赖于感官输入、先前状态与动作。本工作为接口意识提供了严谨的理论框架，使信息处理嵌入到现象学结构之中。该方法契合4E认知观，强调经验的具身性、嵌入性与扩展性。论文由此建立起一个基于范畴数学的、原则性、关系性且现象学导向的人工现象学解释体系。
原文摘要 · Abstract (English)
This paper develops a phenomenology-first approach to artificial consciousness by reframing consciousness as the subjective experience enacted through an agent's interface with the world. We shift the methodological focus to first-person structures, modeled mathematically by categories derived from Q-networks to capture actions and phenomenological invariants. In this framework, Q-networks are conceptualized as relational interfaces encoding agent-world interaction, analogous to how the dynamical states of a computer depend on its sensory inputs, previous states, and actions. Our work provides a rigorous framework for interface consciousness to describe computational systems that embed information-processing into phenomenological structure. The approach aligns with 4E approaches to cognition by emphasizing enactive, embedded, and extended dimensions of experience. The paper thus offers a principled, relational, and phenomenological account of artificial phenomenology grounded in categorical mathematics.
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