Artificial Intelligence with Uncertainty

The link of this ppt is: http://www.intsci.ac.cn/research/lidy04.ppt
When I reviewed the slides about this topic, I was excited. As there was some uncertainty elements related to Grey system theory.

When I studied it, I found lots of useful knowledge. I listed some as follows:

1. Artificial Intelligence with Uncertainty was a new research field in AI.

2. There is a wonderful discuss about the revert theory:

对《还原论》的质疑
如同我们不能从最基础的硅芯片的活动来推测计算机网络上电子邮件的行为一样，我们不可能从分析单个离子、神经元、突触的性质去理解人们欣赏落日美景的感受。因此，我们怎么能够设想从分析单个器官、细胞、基因、蛋白质分子的性质和神经传导就能够推断人脑的认知和思维活动呢？系统论关于系统整体特征不是由低层元素加和而成的原理对还原论提出质疑。

3.It was more difficult playing go with computer than playing chess.

象棋有明确的最终目标状态；围棋没有。
电脑象棋可以从一个目标状态不断搜索最合理的走法（推理）达到下一个目标状态；围棋没有。
电脑象棋可以有目的地向着某一目标状态不断搜索最合理的走法（推理）；围棋没有。
围棋想围住对方，在某个状态下应对的步骤比象棋要多得多，更注重形象思维，更大局观。

4. The research layer of Artificial Intelligence with Uncertainty was natural language. So we, NLP researchers, should be happy with this conclusion :)

5. 追求普遍性、深刻性和富有意义，追求真和美，是基础研究和交叉研究的魅力所在。领略不同学科交汇乃至科学和艺术的交汇所产生的奇妙景观是人生的一大享受。

Grey system is of the uncertain problem. So what is the effect of Grey system in Artificial Intelligence with Uncertainty? It is very interesting.