关于在主动推理中隐含的最小意识理论
Christopher J Whyte1, Andrew W Corcoran2, Jonathan Robinson2
1Monash Centre for Consciousness & Contemplative Studies, Monash University, Melbourne, Australia; Neuroscience Research Theme, School of Medical Sciences, University of Sydney, Australia; Centre for Complex Systems, University of Sydney, Sydney, Australia.
Physics of life reviews
|November 25, 2025
概括
这项研究通过统一从主动推理 (AI) 衍生出来的计算模型,提出了一个最小的意识理论. 人工智能为理解意识和主观经验提供了一个新的框架.
科学领域:
- 认知神经科学 认知神经科学
- 计算精神病学是一种计算精神病学.
- 思想的哲学 思想的哲学
背景情况:
- 由于主观经验的多面性质,研究意识是具有挑战性的.
- 传统的神经科学理论往往侧重于意识的孤立方面,阻碍了比较.
- 现有的理论可能涉及不同的现象,限制重叠和整合.
研究的目的:
- 提出一个最小的,可测试的意识理论.
- 作为一个基础框架,利用主动推断 (AI).
- 在基于AI的意识模型中确定共享的理论承诺.
主要方法:
- 使用主动推理 (AI),这是一个模拟行为的第一原则框架.
- 审查现有工作,将人工智能模型应用于意识研究.
- 从这些模型中合成共同的理论元素.
主要成果:
- 积极推断为意识提供了一个统一的方法.
- 在人工智能意识模型中,有一小部分理论承诺是隐含的.
- 这些承诺表明一个最小的和经验可验证的理论.
结论:
- 一个统一的意识理论可以从积极的推断中出现.
- 这种方法促进了意识理论的比较和整合.
- 拟议的最小理论为未来的研究提供了可测试的路线图.
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