模式识别与人工智能
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模式识别与人工智能  2012, Vol. 25 Issue (3): 456-461    DOI:
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人工智能的突破与科学方法的创新
钟义信
北京邮电大学计算机学院智能科学与网络工程系北京100876
Breakthroughs in Artificial Intelligence and Innovation in Methodology
ZHONG Yi-Xin
Department of Intelligence Science and Network Engineering,School of Computer Science,Beijing University of Posts and Telecommunications,Beijing 100876

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摘要 

最近十年,人工智能理论的研究取得了重要突破:1)发现了智能生成的共性核心机制是在给定条件下的“信息-知识-智能转换”,由此建立了人工智能的机制模拟方法;2)发现了知识的生态学结构是在本能知识支持下的“经验知识-规范知识-常识知识转换”,因而开拓了人工智能研究的视野;3)把智能生成的共性核心机制与知识的生态学结构结合起来,发现原先各自独立发展的人工智能“结构模拟、功能模拟、行为模拟方法分别是机制模拟方法在不同知识条件下的和谐特例”,从而形成了人工智能研究的统一方法和理论,为人工智能的发展开辟了新的前景。文中认为,人工智能研究的上述突破在很大程度上得益于科学研究方法论的创新。

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钟义信
关键词 知识生态机制模拟统一理论科学方法论    
Abstract

The following breakthroughs have been made in the field of artificial intelligence (AI) research over the last decade: 1) The common kernel mechanism of intelligence formation, the information-knowledge-intelligence conversion, was discovered. Thus, the mechanism simulation of intelligence was established. 2)The knowledge ecological structure, the empirical knowledge-regular knowledge-commonsense knowledge growth, which is all supported by innate knowledge, was discovered. 3) The combination of 1) and 2) has led to another discovery that the existing and independent AI approaches, the structural simulation approach to cortex of the brain, the functional simulation approach to the logical thinking, and the behavior simulation approach to the intelligent beings are three special harmonious cases of the mechanism simulation of intelligence under respective knowledge. Therefore, the unified simulation approach and AI theory are achieved, which opens up prospects for AI research. It is believed that the radical source for the breakthroughs in AI is the innovation of scientific methodology.

Key wordsKnowledge Ecology    Mechanism Simulation    Unified Theory    Scientific Methodology   
收稿日期: 2012-02-13     
ZTFLH: TP18  
基金资助:

国家自然科学基金资助项目(No.60873001)

作者简介: 钟义信,男,1940年生,教授,主要研究方向为信息科学与人工智能理论。E-mail:yxzhong@ieeee。org。
引用本文:   
钟义信. 人工智能的突破与科学方法的创新[J]. 模式识别与人工智能, 2012, 25(3): 456-461. ZHONG Yi-Xin. Breakthroughs in Artificial Intelligence and Innovation in Methodology. , 2012, 25(3): 456-461.
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