Unity of Science as Seen Through the Universal Computer

被引：0

作者：

Costa, Jose Felix ^{[1
]}

机构：

[1] Univ Lisbon, Dept Math, Inst Super Tecn, Ctr Filosofia Ciencias, Lisbon, Portugal

来源：

INTERNATIONAL JOURNAL OF UNCONVENTIONAL COMPUTING | 2017年 / 13卷 / 01期

关键词：

Empirical laws; induction; learning theory; philosophy of science; scientific theory; theory unification; INDUCTIVE INFERENCE; IDENTIFICATION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Unification is a common word in Physics as well as in other sciences such as Biology (with the case of natural selection). In this paper, working with basic concepts such as models of empirical scientist that after collecting finitely many experimental observations, comes with a law, and theoretical scientist that after collecting finitely many scientific laws, comes up with a theory, we apply concepts of algorithmic learning theory to shed some light on the concepts of unity and unification common in the philosophy of science, namely that theories (as collections of theorems) established by inductive methods may not be unifiable by inductive methods.

引用

页码：59 / 81

页数：23

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