一个美丽的循环:意识的积极推断理论
Ruben Laukkonen1, Karl Friston2, Shamil Chandaria3
1Faculty of Health, Southern Cross University, Gold Coast, Australia; LIFE, London, UK.
Neuroscience and biobehavioral reviews
|August 1, 2025
概括
积极推理可以通过模拟世界模型来建模意识,使用贝叶斯结合来进行推理选择,并通过反复的信念共享来实现认识深度. 这个框架解释了意识及其变化.
科学领域:
- 认知科学 认知科学
- 神经科学是一个神经科学.
- 人工智能的人工智能
背景情况:
- 意识仍然是理解思想的一个重大挑战.
- 积极推断为建模认知过程提供了一个潜在的框架.
- 现有的模型往往难以捕捉意识体验的动态和整合性质.
研究的目的:
- 提出和验证一个理论模型,其中主动推理可以解释意识.
- 概述积极推理表现有意识属性的必要条件.
- 介绍"美丽的循环理论"作为意识建模的正式化.
主要方法:
- 定义模型意识的积极推理的三个条件:世界模型模拟,推理竞争 (贝叶斯结合) 和认识深度.
- 提出了一个超级模型,用于精确控制,以管理推理层.
- 描述在等级系统中共享信仰的递归性质.
主要成果:
- 积极推断可以模拟知识和行动的世界模型 (认识领域).
- 贝叶斯结合,通过推理竞争,选择减少不确定性的推理,类似于有意识的选择.
- 知识深度使世界模型能够掌握其自身存在的知识 (现场证明).
结论:
- 拟议的"美丽循环理论"整合了主动推断,贝叶斯原则和层次处理来建模意识.
- 这个框架提供了对一般智力,改变意识状态和冥想的见解.
- 积极推断提供了一种可行的计算方法来理解意识的机制.
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