Kolmogorov-Chaitin复杂性的稳定定义
Towards a stable definition of Kolmogorov-Chaitin complexity
摘要：
虽然信息内容在加法常数之前是不变的，但适用于程序设计语言的可能加法常数的范围是如此之大，以至于在实际计算K（s）时，它起着重要的作用，K（s）是字符串s的Kolmogorov-Chaitin复杂度。人们曾试图通过诉诸语言的“自然性”来达到一个足够稳定的框架，以给出K的具体定义，而不依赖于程序设计语言下的任何常数。本文的目的是提出一种方法来克服这个问题，通过寻找一组模型的计算收敛在输出概率分布，这样，“自然性”可以推断，从而提供了一个框架下的收敛模型的计算K的稳定定义。
英文摘要：
Although information content is invariant up to an additive constant, the range of possible additive constants applicable to programming languages is so large that in practice it plays a major role in the actual evaluation of K(s), the Kolmogorov-Chaitin complexity of a string s. Some attempts have been made to arrive at a framework stable enough for a concrete definition of K, independent of any constant under a programming language, by appealing to the "naturalness" of the language in question. The aim of this paper is to present an approach to overcome the problem by looking at a set of models of computation converging in output probability distribution such that that "naturalness" can be inferred, thereby providing a framework for a stable definition of K under the set of convergent models of computation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
