Learning incommensurate concepts

被引:0
作者
Clatterbuck, Hayley [1 ]
Gentry, Hunter [2 ]
机构
[1] Rethink Prior, San Francisco, CA 94117 USA
[2] Kansas State Univ, Manhattan, KS 66506 USA
关键词
Machine learning; Concepts; Incommensurability; Bootstrapping; LANGUAGE; CATEGORIZATION; ORIGINS; SPACES;
D O I
10.1007/s11229-024-04883-7
中图分类号
N09 [自然科学史]; B [哲学、宗教];
学科分类号
01 ; 0101 ; 010108 ; 060207 ; 060305 ; 0712 ;
摘要
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.
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收藏
页数:36
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