귀납법과 수학적 귀납법
On Induction and Mathematical Induction
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초록
21세기 세상은 제4차 산업혁명의 영향으로 인하여 새로운 산업사회로 변모하고 있으며 과학적 방법론을 전제하는 데이터과학과 함께 인공지능 시대로의 전환이 진행되고 있다. 이에 데이터를 다루고 지식과 통찰력을 도출하기 위한 논리에 대한 탐구가 요구된다. 논리는 크게 연역법과 귀납법으로 나뉜다. 수학이나 인공지능에 사용하는 알고리즘은 연역적 논리를 기반으로 하는 한편 과학은 귀납적 논리를 사용한다. 특히 확률론의 발전에 관한 고찰은 인공지능의 딥러닝 기술에 의미를 더해줄 수 있다. 더불어 알고리즘에 이용되는 재귀 또는 점화식에 적용되는 논리인 수학적 귀납법에 대한 고찰도 필요하다. 본 연구는 데이터과학과 인공지능의 발전을 위하여 논리,특히 귀납논리와 수학적 귀납법, 과학적 방법론의 기원과 의미를 살펴본다.
Abstract
The 21st century world has experienced all-around changes from the 4th industrial revolution. In this developmental changes, artificial intelligence is at the heart, with data science adopting certain scientific methods and tools on data. It is necessary to investigate on the logic lying underneath the methods and tools. We look at the origins of logic, deduction and induction, and scientific methods, together with mathematical induction, probabilistic method and data science, and their meaning.
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