推論の空間的理論<br>Space to Reason : A Spatial Theory of Human Thought (The Mit Press) -- Hardback

推論の空間的理論
Space to Reason : A Spatial Theory of Human Thought (The Mit Press) -- Hardback

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  • 製本 Hardcover:ハードカバー版/ページ数 290 p./サイズ 16 illus.
  • 言語 ENG
  • 商品コード 9780262018654
  • DDC分類 153.43

基本説明

An argument against the role of visual imagination in resoning that proposes a spatial theory of human thought, supported by empirical and computational evidence.

Full Description


An argument against the role of visual imagination in reasoning that proposes a spatial theory of human thought, supported by empirical and computational evidence.Many scholars believe that visual mental imagery plays a key role in reasoning. In Space to Reason, Markus Knauff argues against this view, proposing that visual images are not relevant for reasoning and can even impede the process. He also argues against the claim that human thinking is solely based on abstract symbols and is completely embedded in language. Knauff proposes a third way to think about human reasoning that relies on supramodal spatial layout models, which are more abstract than pictorial images and more concrete than linguistic representations. He argues that these spatial layout models are at the heart of human thought, even thought about nonspatial relations in the world. For Knauff the visual images that we so often associate with reasoning are only in the foreground of conscious experience. Behind the images, the actual logical work is carried out by reasoning-specific operations on these spatial layout models. Knauff also offers a solution to the problem of indeterminacy in human reasoning, introducing the notion of a preferred layout model, which is one layout model among others that has the best chance of being mentally constructed and thus guides the further process of thought. Knauff's "space to reason" theory covers the functional, the algorithmic, and the implementational level of analysis and is corroborated by psychological experiments, functional brain imaging, and computational modeling.

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