arXiv 1303.20132013-03-08cs.AI

作为压缩的计算：智能的SP理论

Computing as compression: the SP theory of intelligence

J Gerard Wolff

备注：: 8 pages, 2 figures. arXiv admin note: text overlap with arXiv:1212.0229

摘要：

本文概述了SP智能理论及其核心思想，即人工智能、主流计算以及人类的许多感知和认知都可以理解为信息压缩。描述了SP理论的背景和起源，以及该理论的主要元素，包括从生物信息学中借用但具有重要差异的多重比对的关键概念。与SP理论相关联的是这样一种思想，即信息中的冗余可以被理解为模式的重复，信息的压缩可以通过模式的匹配和统一（合并）来实现，并且计算和信息压缩基本上都是概率性的。看来SP系统是图灵等价的，在这个意义上，任何可以用图灵机计算的东西，原则上也可以用SP机计算。SP理论和多重对齐概念的主要优势之一是在人工智能中对概念和现象进行建模。在该领域内，SP理论提供了一种简单但通用的表示不同种类知识的方法，它可以对自然语言的解析和产生进行建模，具有理解和翻译自然语言的潜力，它在模式识别方面具有优势，在计算机视觉方面具有潜力，它可以对几种推理进行建模，并且它具有规划，解决问题，和无监督学习。本文包括两个例子，展示了如何替代解析的一个歧义句可能被建模为多重对齐，以及另一个例子，展示了如何多重对齐的概念可以应用于医疗诊断。

英文摘要：

This paper provides an overview of the SP theory of intelligence and its central idea that artificial intelligence, mainstream computing, and much of human perception and cognition, may be understood as information compression. The background and origins of the SP theory are described, and the main elements of the theory, including the key concept of multiple alignment, borrowed from bioinformatics but with important differences. Associated with the SP theory is the idea that redundancy in information may be understood as repetition of patterns, that compression of information may be achieved via the matching and unification (merging) of patterns, and that computing and information compression are both fundamentally probabilistic. It appears that the SP system is Turing-equivalent in the sense that anything that may be computed with a Turing machine may, in principle, also be computed with an SP machine. One of the main strengths of the SP theory and the multiple alignment concept is in modelling concepts and phenomena in artificial intelligence. Within that area, the SP theory provides a simple but versatile means of representing different kinds of knowledge, it can model both the parsing and production of natural language, with potential for the understanding and translation of natural languages, it has strengths in pattern recognition, with potential in computer vision, it can model several kinds of reasoning, and it has capabilities in planning, problem solving, and unsupervised learning. The paper includes two examples showing how alternative parsings of an ambiguous sentence may be modelled as multiple alignments, and another example showing how the concept of multiple alignment may be applied in medical diagnosis.

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。

摘要：

英文摘要：

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