Learning incommensurate concepts.
A central task of developmental psychology and philosophy of science is to show how humans learn radically new concepts. Famously, Fodor has argued that such learning is impossible if concepts have definitional structure and all learning is hypothesis testing. We present several learning processes t...
| Publicado en: | Synthese Vol. 205; no. 3; pp. 1 - 37 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Mar2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=183305300&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 183305300 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Mar2025 vid: 205 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 183305300 10.1007/s11229-024-04883-7 ppf: 1 ppct: 36 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.9MB tig: atl: Learning incommensurate concepts. aug: au: Clatterbuck, Hayley Gentry, Hunter affil: Rethink Priorities, San Francisco, CA, USA https://ror.org/05p1j8758 Kansas State University, Manhattan, KS, USA sug: keyword: Bootstrapping Concepts Incommensurability Machine learning ab: A central task of developmental psychology and philosophy of science is to show how humans learn radically new concepts. Famously, Fodor has argued that such learning is impossible if concepts have definitional structure and all learning is hypothesis testing. We present several learning processes that can generate novel concepts. They yield transformations of the fundamental feature space, generating new similarity structures which can underlie conceptual change. This framework provides a tractable, empiricist-friendly account that unifies and shores up various strands of the neo-Quinean approach to conceptual development. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2025. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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