• Journal for History of Mathematics
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• v.15 no.3
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• pp.75-82
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• 2002

G$\ddot{o}$del's metamathematical program from Incompleteness to Speed-up theorems shows the necessity of ever higher systems beyond the fixed formal system and devises the relative consistency.

• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.258-263
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• 1995

마음과 기계의 관계에 대한 $G{\ddot{o}}del's$의 선언결론(disjunctive conclusion)은 마음과 정보처리형식체계의 논리적 동치성을 함의하고 있다. 그리고 $G{\ddot{o}}del's$의 불완전성 정리(Incompleteness Theorems)에 따르면 마음과 정보처리형식체계의 논리적 동치성은 무모순이며, 동치성 반증의 이론은 그 모델을 가질 수 없다.

• Korean Journal of Logic
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• v.21 no.1
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• pp.97-133
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• 2018

In his unpublished article, "Is Mathematics Syntax of Language?," $G{\ddot{o}}del$ criticizes what he calls the 'syntactical interpretation' of mathematics by Carnap. Park, Chun, Awodey and Carus, Ricketts, and Tennant have all reconstructed $G{\ddot{o}}del^{\prime}s$ arguments in various ways and explored Carnap's possible responses. This paper first recreates $G{\ddot{o}}del$ and Carnap's debate about the nature of mathematics. After criticizing most existing reconstructions, I claim to make the following contributions. First, the 'language relativity' several scholars have attributed to Carnap is exaggerated. Rather, the essence of $G{\ddot{o}}del^{\prime}s$ critique is the applicability of mathematics and the argument based on 'expectability'. Thus, Carnap's response to $G{\ddot{o}}del$ must be found in how he saw the application of mathematics, especially its application to science. I argue that the 'correspondence principle' of Carnap, which has been overlooked in the existing discussions, plays a key role in the application of mathematics. Finally, the real implications of $G{\ddot{o}}del^{\prime}s$ incompleteness theorems - the inexhaustibility of mathematics - turn out to be what both $G{\ddot{o}}del$ and Carnap agree about.

• Journal for History of Mathematics
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• v.22 no.3
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• pp.31-44
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• 2009

Anyone wishing to understand cognitive science, a converging science, need to become familiar with three major mathematical landmarks: Turing machines, Neural networks, and $G\ddot{o}del's$ incompleteness theorems. The present paper aims to explore the mathematical foundations of cognitive science, focusing especially on these historical landmarks. We begin by considering cognitive science as a metamathematics. The following parts addresses two mathematical models for cognitive systems; Turing machines as the computer system and Neural networks as the brain system. The last part investigates $G\ddot{o}del's$ achievements in cognitive science and its implications for the future of cognitive science.