作为可交换情感-认知推断的意识贝叶斯理论
Bayesian Theory of Consciousness as Exchangeable Emotion-Cognition Inference
AI总结：
本文提出统一框架EITC，将意识建模为情感与认知交互的递归推断过程，结合贝叶斯大脑假说与最优传输，通过潜在情感自我模型实现体验整合与分化。
摘要：
本文提出了一个统一框架，其中意识作为一种循环一致且情感锚定的推断过程而涌现，并由情感与认知的交互递归地构建。借鉴信息论、最优传输和贝叶斯大脑假说，我们将情感形式化为低维结构先验，将认知形式化为特异性实例化更新。这种情感-认知循环通过将情感加权先验与情境敏感的认知评估对齐，最小化联合不确定性。因此，主观体验作为时间上延展的、情感调节的模拟的信息足迹而产生。我们引入了意识可交换整合理论（EITC），将意识片段建模为从潜在情感自我模型中提取的条件可交换样本。该潜在变量通过具有非零不可还原性的统一因果结构支持整合，并通过保留跨片段的情境特异性支持分化。我们通过Rao-Blackwellized推断将该架构与意识的贝叶斯理论联系起来，通过边缘化潜在自我结构稳定推断，同时实现自适应更新。该机制确保连贯性，防止推断坍塌，并支持目标导向模拟。该形式化框架建立在De Finetti可交换性定理、整合信息理论和KL正则化最优传输之上。总体而言，意识被重新构建为递归推断过程，由情感塑造，由认知精炼，通过可交换性稳定，并通过跨时间整合体验的潜在自我模型统一。
英文摘要：
This paper proposes a unified framework in which consciousness emerges as a cycle-consistent, affectively anchored inference process, recursively structured by the interaction of emotion and cognition. Drawing from information theory, optimal transport, and the Bayesian brain hypothesis, we formalize emotion as a low-dimensional structural prior and cognition as a specificity-instantiating update. This emotion-cognition cycle minimizes joint uncertainty by aligning emotionally weighted priors with context-sensitive cognitive appraisals. Subjective experience thus arises as the informational footprint of temporally extended, affect-modulated simulation. We introduce the Exchangeable Integration Theory of Consciousness (EITC), modeling conscious episodes as conditionally exchangeable samples drawn from a latent affective self-model. This latent variable supports integration, via a unified cause-effect structure with nonzero irreducibility, and differentiation, by preserving contextual specificity across episodes. We connect this architecture to the Bayesian theory of consciousness through Rao-Blackwellized inference, which stabilizes inference by marginalizing latent self-structure while enabling adaptive updates. This mechanism ensures coherence, prevents inference collapse, and supports goal-directed simulation. The formal framework builds on De Finetti's exchangeability theorem, integrated information theory, and KL-regularized optimal transport. Overall, consciousness is reframed as a recursive inference process, shaped by emotion, refined by cognition, stabilized through exchangeability, and unified through a latent self-model that integrates experience across time.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
