文章基本信息

标题：「過剰性」とプロジェクション
本地全文：下载
作者：嶋田総太郎
期刊名称：認知科学
印刷版ISSN：1341-7924
电子版ISSN：1881-5995
出版年度：2021
卷号：28
期号：2
页码：217-221
DOI：10.11225/cs.2021.002
出版社：Japanese Cognitive Science Society
摘要：Ikegami (2021) proposes to reinstate excessiveness as a critical subject in cognitive science. In this commentary, I will discuss what this excessiveness is, taking a hint from the philosophies of Merleau-Ponty and Henry. When we create representations from bodily information, it is impossible to make representations of all the information we receive, and what leaks out here should be called “excessiveness”. In this context, the possibility of being able to handle phenomena that are difficult to verbalize, such as qualia and affectivity, emerges. Furthermore, in relation to deep learning, I would like to discuss contraction and expansion of the representation. Autoencoder is a technology for compressing data while maintaining the original information, and can be divided into an encoder part that compresses the input into latent variables, and a decoder (generator) part that restores the original information by appropriately expanding the latent variables. Generative deep learning is an extension of the generator, which can reconstruct information from appropriate latent variables. I would like to consider how this generative deep learning can regenerate excessiveness from contracted representation and discuss the relationship between the generator and cognitive projection.
关键词：過剰性;クオリア;情感性;潜在空間;認知的プロジェクション;身体性認知科学;excessiveness;qualia;affectivity;latent space;cognitive projection;embodied cognitive science