北京航空航天大学学报社科版 ›› 2021, Vol. 34 ›› Issue (2): 99-104.DOI: 10.13766/j.bhsk.1008-2204.2021.0003

• 哲学与文化 • 上一篇    下一篇

机器学习与科学发现的逻辑刍议

王东   

  1. 北京工商大学 马克思主义学院, 北京 100048
  • 收稿日期:2021-01-06 发布日期:2021-04-02
  • 作者简介:王东(1983—),安徽合肥人,讲师,博士,研究方向为一般科学哲学、人工智能哲学、认知科学哲学.
  • 基金资助:
    国家社会科学基金重大项目(17ZDA028,20&ZD044)

A Preliminary Study of Machine Learning and Logic of Scientific Discovery

WANG Dong   

  1. School of Marxism, Beijing Technology and Business University, Beijing 100048, China
  • Received:2021-01-06 Published:2021-04-02

摘要: 是否存在科学发现的逻辑一直存在争议,人工智能(AI)发展早期通过基于规则的和大规模数据挖掘的方法探索自动科学发现存在局限,包括需要先验知识或者只能发现特定领域的经验规律。通过近期两个案例分析介绍基于机器学习的研究可以不需要先验知识就能发现科学概念甚至是简单的理论,但仍然存在训练数据的来源、观察和实验的选择、科学理论的构建以及因果建模等问题,需要结合科学哲学和哲学史做跨学科的研究。

关键词: 机器学习, 自动科学发现, 科学发现的逻辑, 智能驱动, 科学概念

Abstract: Whether there is the logic of scientific discovery has always been controversial. In the early development of artificial intelligence (AI), there were limitations in the research of automatic scientific discovery through rule-based and data mining methods, including the need for prior knowledge or only the discovery of empirical laws in specific fields. Through two case studies, it was shown that the recent research based on machine learning can find the concept of science and even a simple theory without prior knowledge. But there are still some problems such as the source of training data, the choice of observation and experiment, the construction of scientific theory and the causal modeling which need interdisciplinary research combination with philosophy of science and history of philosophy.

Key words: machine learning, auto-discovery, logic of scientific discovery, AI-driven, scientific concept

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