2008/04/09

Minsky!

在床上隨便翻 Booch 的《Object-Oriented Analysis and Design with Applications》2/e,翻到 Third Section: Applications 的開場引言:

To build a theory, one needs to know a lot about the basic phenomena of the subject matter. We simply do not know enough about these, in the theory of computation, to teach the subject very abstractly. Instead, we ought to teach more about the particular examples we now understand thoroughly, and hope that from this we will be able to guess and prove more general principles.

說這番話的人是 M. Minsky,碰過 AI 的人都一定認識他。這番話本身則是從 Minsky 的 1969 年 Turing Award Lecture〈Form and Content in Computer Science〉出來的。這就是 program derivation 觸礁的原因嗎?我現在的感覺是 categorical approach 的理論很重,可是實用上卻沒發揮相稱的威力,感覺上捕捉到的原則還不夠。當然這可能只是我還沒上手才有的錯覺,也可能是演算法本質上就比較複雜 ─ 比較對象當然是數學主要探討的數與形。但 Minsky 講的也是很有可能的情況,畢竟數學發展了一兩千年才有今日的面貌,中間對概念的發掘與解析所下的工夫鐵定不少。

我順著看下去,馬上又看到一段很有趣的論述:

It is instructive to consider the analogy with physics, in which one can organize much of the basic knowledge as a collection of rather compact conservation laws. This, of course, is just one kind of description; [...] there are many ways to formulate things and it is risky to become too attached to one particular form or law and come to believe that it is the real basic principle.

這基本上就是我先前簡單討論「正式與直覺的二元論」以及 "introspection framework of theories" 想講的東西。Minsky 看來就比較擅長哲學論述,概念刻畫的粒度夠細,這篇 lecture 值得一讀 XD。

如果對照一下我比較早期和大三以來的 blog posts,會發現我的這種哲學論述少了很多。這其實不代表我對此類議題的思考變少了,而是我覺得這種抽象的討論必然奠基於實際的經驗上,而我顯然還很欠缺後者。沒有基礎的抽象論述我覺得其實就平淡無奇,稍微多想一點大概就想得到,所以把它們當寶寫出來有點愚蠢。例如我剛剛說「抽象討論奠基於實際經驗」,這句話根本(差不多)是最簡單的 tautology:「抽象」依定義就是「從具象萃取出來的」。我現在其實又覺得大學部的不用想太多,乖乖把功課讀好就行,等經驗累積夠多之後想一下就通了。不然像我現在看一套理論,一下子就覺得它只是一種表述形式(或許是很美的一種),不會賦予它什麼特別地位。啊算了,我懶得整理思緒了 XD。

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形上觀等幾十年後再來談吧 XD。

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