From Micro-Worlds to Knowledge Representation : AI at an Impasse Hubert L. Dreyfus 15. Oct. 2002 Presented by BoYun Eom

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

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

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.

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

< 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..

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.

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

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.

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

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.

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...

< 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

< 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?

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

< 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 10. ...

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