摘要
人工智能是一门交叉学科,融合了脑认知科学、心理学、数学(包括统计学)、信息科学、计算机科学等诸多学科.目前,以大数据驱动的深度学习为代表的人工智能发展迅速,在许多领域有广泛的应用.但是,人工智能现在最大的缺陷是没有理论,基本上还处于实验科学阶段.探讨人工智能的机理,进行其理论研究,对人工智能的进一步发展至关重要.为了揭示人工智能的本质,进一步促进人工智能的理论研究,本文从认知生物学和认知心理学两个层面,探讨现有的三个主要的人工智能学派—联结主义、符号主义和行为主义—所蕴含的机理和具体实现的数学理论和方法,试图解释人工智能的本质,给出未来可解释的和具有创造性的人工智能的一些可能的基础研究方法和研究方向.
Artificial intelligence is an interdisciplinary discipline that integrates many subjects, such as brain cognitive science, psychology, mathematics(including statistics), information science, and computer science. At present, artificial intelligence represented by big data-driven deep learning has developed rapidly and has been widely used in many fields. However, the biggest flaw in artificial intelligence right now is that it has no theory and is basically still in the experimental science stage. To explore the mechanism of artificial intelligence and carry out its theoretical research is of vital importance to the further development of artificial intelligence. To reveal the nature and promote the theoretical research of artificial intelligence, the mechanisms and concrete realizations of the three existing artificial intelligence schools are explored from the two levels of cognitive biology and cognitive psychology, such as symbolism, connectionism and behaviorism, trying to explain the nature of artificial intelligence. Some possible basic research methods and research directions of future interpretable and creative artificial intelligence are proposed.
作者
郭田德
韩丛英
Tiande Guo;Congying Han
出处
《中国科学:数学》
CSCD
北大核心
2020年第11期1541-1578,共38页
Scientia Sinica:Mathematica
基金
国家自然科学基金(批准号:11731013,11991022和U19B2040)资助项目。
关键词
人工智能
数学
认知生物学
认知心理学
artificial intelligence
mathematics
cognitive biology
cognitive psychology