了解大脑作为一个具有符号接地功能的精神化机器.
Takaaki Kaneko1,2, Taihei Ninomiya3,2, Masaki Isoda1,2
1Division of Behavioral Development, Department of System Neuroscience, National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Aichi 444-8585, Japan kanekot@nips.ac.jp isodam@nips.ac.jp.
这篇评论提出了心理化的计算机制,即推断他人的心理状态的能力. 符号接地增强了这一过程,改善了对他人的行动的预测.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 人工智能的人工智能
背景情况:
- 从感官信息中推断他人的隐藏精神状态,对社会认知至关重要.
- 预测编码框架解释了大脑如何通过尽量减少预测错误来推断隐藏状态.
研究的目的:
- 提出心理化背后的计算机制.
- 审查参与这些计算过程的神经基质.
- 探索符号接地在提高心理效率和可靠性的作用.
主要方法:
- 审查现有的关于思维化和预测编码的文献.
- 计算机制的理论建议,用于心智化.
- 带有和没有符号接地的人工智能化系统的初步模拟.
主要成果:
- 精神化可能独特地涉及到在主观可体验的心理空间中代表他人的状态,解决符号接地问题.
- 符号接地提高了推断他人的心理状态的效率和可靠性.
- 模拟的人工智能化系统与符号接地优于纯贝叶斯观察员在预测虚拟代理行动.
结论:
- 预测编码的计算框架,加上符号接地,为理解思维提供了一个有希望的模型.
- 整合人工和生物神经网络的未来研究可以阐明社会认知的神经算法.
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