1. From Micro-Worlds to Knowledge Representation : AI at an Impasse Hubert L. Dreyfus Oct Presented by BoYun Eom

2. OUTLINE The Early Seventies : Micro-Worlds - SHRDLU - SEE - ARCH
- SOME EXCELLENT PROGRAMS
The Later Seventies : Knowledge Representation
- FRAME
- SCRIPT
- KRL
Conclusion

3. The Early Seventies : Micro-Worlds
How much could be done with as little knowledge as possible?

4. SHARDLU – Winograd, 1972
Most impressive new achievement in the early seventies.
Natural language understanding program in a limited domain.
An integrated system which makes use of syntax, semantics, and facts about blocks.
The discussion of owning.

5. < Sample Process >
“ Pick up a big red block. ”
“ OK! ”
“ Grasp the pyramid ”
“ I don’t understand which pyramid you mean.”

6. < Sample Process For Owning >
“ What is the pyramid supported by? ”
“ The box ”
“ I own blocks which are not red, but I don’t own anything which supports a pyramid. ”
“ I understand.”
“ Do I own the box? ”
“ No.”
==> SHRDLU knows what it owns, but doesn’t understand what it is to own something..

7. SEE – David Waltz, 1972 Adolfo Guzman’s SEE program (1968) :
- Analyzing two-dimensional projections of
complicated three-dimensional “scenes”.
- Having serious limitation.
David Waltz’s program :
- Generalizing Guzman’s method.
- A much more powerful vision system.
It could not provide the way of thinking about general intelligent system.

8. ARCH – Winston, 1970
Formal model of everyday learning and categorization
Selected and preweighted primitives : illustrating the possibilities and essential limitations of micro-worlds.

9. Some Excellent Programs
Well circumscribed domain : with all the significant facts, questions and comparatively small set of explicit rules - “a micro-world”
Examples :
- Chess
- Feigenbaum’s program for analyzing certain
kinds of mass spectroscopy data (1977)
- Shortliffe’s program for assisting in the
diagnosis and treatment of some deases (1976)
Those are not the achievement of genuine artificial intelligence.

10. The Later Seventies : Knowledge Representation
How to structure and retrieve information, in situations where anything might be relevant?

11. Frames : Minsky, 1974
A data-structure for representing a stereotyped situation.
Similar to Husserl’s for representing everyday knowledge.
Top levels : Fixed and representing things that are always true about the supposed situation.
Lower levels : having many terminal-”slots”
Having brought the problem of how to represent our everyday knowledge into the open in AI.

12. Scripts : Schank
Using frames as part of a special-purpose micro-world analysis dealing with commonsense knowledge.
Description language : consisting of eleven primitive acts
ex ) ATRANS, PTRANS, INGEST...

13. < Illustration of the restaurant script >
Script : restaurant
Roles : customers; waitress; chef; cashier
Reason : to get food so as to go down in hunger and up in pleasure
Scene 1 entering
PTRANS - go into restaurant
MBUILD - find table
PTRANS - go to table
MOVE - sit down
Scene 2 ordering
ATRANS - receive menu
ATTEND - look at it
MBUILD - decide on order
MTRANS - tell order to waitress

14. < Skepticism >
Abnormal ways everyday activities can break down.
Program has not understood a restaurant story the way people in our culture do.
- Did the customer eat his food with his
nose?

15. KRL : Terry Winograd
Symbolic descriptions of multidimensional prototypical objects whose relevant aspects are a function of their context.
The difficulty of matching process :
there must be finite set of prototypes to be matched.
Frame selection problem : we cannot take all of our possible frames for different kinds of events

16. < Descriptions for a prototypical bachelor >
The Word “bachelor” ?
1. A person
2. A male
3. An adult
4. Not currently officially married
5. Not in a marriage-like living sutuation
6. Potentially marriageable
7. Leading a backelor-like life style
8. Not having been married previously
9. Having an intention, at least temporarily, not to marry

17. Conclusion
“Knowledge” of human interests and practices need not be represented at all (?)
The basis of human intelligence cannot be isolated and explicitly understood (?)
“Man can embody the truth, but he cannot know it” - Yeats