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不确定性人工智能
引用本文:李德毅,刘常昱,杜鹢,韩旭.不确定性人工智能[J].软件学报,2004,15(11):1583-1594.
作者姓名:李德毅  刘常昱  杜鹢  韩旭
作者单位:1. 中国电子工程系统研究所,北京,100840
2. 中国人民解放军理工大学,江苏,南京,210007
3. 中国电子设备系统工程公司,北京,100840
基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60375016, 60496323 (国家自然科学基金)
摘    要:在主、客观世界普遍存在的不确定性中,随机性和模糊性是最重要的两种形式.研究了随机性和模糊性之间的关联性,统一用熵作为客观事物和主观认知中不确定状态的度量,用超熵来度量不确定状态的变化,并利用熵和超熵进一步研究了混沌、分形和复杂网络中的不确定性,以及由此带来的种种进化和变异,为实现不确定性人工智能找到了一种简单、有效的形式化方法,也为包括形象思维在内的不确定性思维的自动化打下了基础.不确定性人工智能是人工智能进入21世纪的新发展.这个由多学科交叉渗透构成的新学科,必将使得机器能够具备人脑一样的不确定性信息和知识的表示能力、处理能力和思维能力.

关 键 词:  超熵  混沌  分形  复杂网络  幂律分布
文章编号:1000-9825/15(11)1583
收稿时间:2004/7/13 0:00:00
修稿时间:2004年7月13日

Artificial Intelligence with Uncertainty
LI De-Yi,LIU Chang-Yu,DU Yi and HAN Xu.Artificial Intelligence with Uncertainty[J].Journal of Software,2004,15(11):1583-1594.
Authors:LI De-Yi  LIU Chang-Yu  DU Yi and HAN Xu
Abstract:Uncertainty exists widely in the subjective and objective world. In all kinds of uncertainty, randomness and fuzziness are the most important and fundamental. In this paper, the relationship between randomness and fuzziness is discussed. Uncertain states and their changes can be measured by entropy and hyper-entropy respectively. Taken advantage of entropy and hyper-entropy, the uncertainty of chaos, fractal and complex networks by their various evolution and differentiation are further studied. A simple and effective way is proposed to simulate the uncertainty by means of knowledge representation which provides a basis for the automation of both logic and image thinking with uncertainty. The AI (artificial intelligence) with uncertainty is a new cross-discipline, which covers computer science, physics, mathematics, brain science, psychology, cognitive science, biology and philosophy, and results in the automation of representation, process and thinking for uncertain information and knowledge.
Keywords:entropy  hyper-entropy  chaos  fractal  complex network  power-law distribution
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