---------- Date: 28 May 84 12:55:37-PDT (Mon) From: hplabs!hao!seismo!cmcl2!floyd!vax135!cornell!jqj @ Ucb-Vax.arpa Subject: Re: KS300 Question Article-I.D.: cornell.195 KS300 is owned by (and a trademark of) Teknowledge, Inc. Although it is largeley based on Emycin, it was extensively reworked for greater maintainability and reliability, particularly for Interlisp-D environments (the Emycin it was based on ran only on DEC-20 Interlisp). Teknowledge can be reached by phone (no net address, I think) at (415) 327-6600. ------------------------------ Date: Wed 30 May 84 19:41:17-PDT From: Dikran Karagueuzian Subject: CSLI Report [Forwarded from the CSLI newsletter by Laws@SRI-AI.] New CSLI-Report Available ``Lessons from Bolzano'' by Johan van Benthem, the latest CSLI-Report, is now available. To obtain a copy of Report No. CSLI-84-6, contact Dikran Karagueuzian at 497-1712 (Casita Hall, Room 40) or Dikran at SU-CSLI. ------------------------------ Date: Thu 31 May 84 11:15:35-PDT From: Al Davis Subject: Hardware Prototyping On the issue of the Stone - Shaw wars. I doubt that there really is a viable "research paradigm shift" in the holistic sense. The main problem that we face in the design of new AI architectures is that there is a distinct possibility that we can't let existing ideas simply evolve. If this is true then the new systems will have to try to incorporate a lot of new strategies which create a number of complex problems, i.e. 1. Each new area means that our experience may not be valid. 2. Interactions between these areas may be the problem, rather than the individual design choices - namely efficient consistency is a difficult thing to achieve. In this light it will be hard to do true experiments where one factor gets isolated and tested. Computer systems are complex beasts and the problem is even harder to solve when there are few fundamental metrics that can be applied microscopically to indicate success or failure. Macroscopically there is always cost/performance for job X, or set of tasks Y. The experience will come at some point, but not soon in my opinion. It will be important for people like Shaw to go out on a limb and communicate the results to the extent that they are known. At some point from all this chaos will emerge some real experience that will help create the future systems which we need now. I for one refuse to believe that an evolved Von Neumann architecture is all there is. We need projects like DADO, Non-Von, the Connection Machine, ILLIAC, STAR, Symbol, the Cosmic Cube, MU5, S1, .... this goes on for a long time ..., --------------- if given the opportunity a lot can be learned about alternative ways to do things. In my view the product of research is knowlege about what to do next. Even at the commercial level very interesting machines have failed miserably (cf. B1700, and CDC star) and rather Ho-Hum Dingers (M68000, IBM 360 and the Prime clones) have been tremendous successes. I applaud Shaw and company for giving it a go along with countless others. They will almost certainly fail to beat IBM in the market place. Hopefully they aren't even trying. Every 7 seconds somebody buys an IBM PC - if that isn't an inspiration for any budding architect to do better then what is? Additionally, the big debate over whether CS or AI is THE way is absurd. CS has a lot to do with computers and little to do with science, and AI has a lot to do with artificial and little to do with intelligence. Both will and have given us something worthwhile, and a lot of drivel too. The "drivel factor" could be radically reduced if egotism and the ambition were replaced with honesty and responsibility. Enough said. Al Davis FLAIR ------------------------------ Date: Mon, 28 May 84 14:28:32 PDT From: Charlie Crummer Subject: Identity The thing about sameness and difference is that humans create them; back to the metaphor and similie question again. We say, "Oh, he's the same old Bill.", and in some sense we know that Bill differs from "old Bill" in many ways we cannot know. (He got a heart transplant, ...) We define by declaration the context within which we organize the set of sensory perceptions we call Bill and within that we recognize "the same old Bill" and think that the sameness is an attribute of Bill! No wonder the eastern sages say that we are asleep! [Read Hubert Dreyfus' book "What Computers Can't Do".] --Charlie ------------------------------ Date: Wed, 30 May 1984 16:15 EDT From: MONTALVO%MIT-OZ@MIT-MC.ARPA Subject: A restatement of the problem (phil/ai) From: (Alan Wexelblat) decvax!ittvax!wxlvax!rlw @ Ucb-Vax Suppose that, while touring through the grounds of a Hollywood movie studio, I approach what, at first, I take to be a tree. As I come near to it, I suddenly realize that what I have been approaching is, in fact, not a tree at all but a cleverly constructed stage prop. So, let me re-pose my original question: As I understand it, issues of perception in AI today are taken to be issues of feature-recognition. But since no set of features (including spatial and temporal ones) can ever possibly uniquely identify an object across time, it seems to me (us) that this approach is a priori doomed to failure. Spatial and temporal features, and other properties of objects that have to do with continuity and coherence in space and time DO identify objects in time. That's what motion, location, and speed detectors in our brains to. Maybe they don't identify objects uniquely, but they do a good enough job most of the time for us to make the INFERENCE of object identity. In the example above, the visual features remained largely the same or changed continuously --- color, texture normalized by distance, certainly continuity of boundary and position. It was the conceptual category that changed: from tree to stage prop. These latter properties are conceptual, not particularly visual (although presumably it was minute visual cues that revealed the identity in the first place). The bug in the above example is that no distiction is made between visual features and higher-level conceptual properties, such as what a thing is for. Also, identity is seen to be this unitary thing, which, I think, it is not. Similarities between objects are relative to contexts. The above stage prop had spatio-termporal continuity (i.e., identity) but not conceptual continuity. Fanya Montalvo ------------------------------ Date: Wed, 30 May 84 09:18 EDT From: Izchak Miller Subject: The experience of cross-time identity. A follow-up to Rosenberg's reply [greatings, Jay]. Most commentators on Alan's original statement of the problem have failed to distinguish between two different (even if related) questions: (a) what are the conditions for the cross-time (numerical) identity of OBJECTS, and (b) what are the features constitutive of our cross-time EXPERIENCE of the (numerical) identity of objects. The first is an ontological (metaphysical) question, the second is an epis- temological question--a question about the structure of cognition. Most commentators addressed the first question, and Rosenberg suggests a good answer to it. But it is the second question which is of importance to AI. For, if AI is to simulate perception, it must first find out how perception works. The reigning view is that the cross-time experience of the (numerical) identity of objects is facilitated by PATTERN RECOGNITION. However, while it does indeed play a role in the cognition of identity, there are good grounds for doubting that pattern recognition can, by itself, account for our cross-time PERCEPTUAL experience of the (numerical) sameness of objects. The reasons for this doubt originate from considerations of cases of EXPERIENCE of misperception. Put briefly, two features are characteristic of the EXPERIENCE of misperception: first, we undergo a "change of mind" regar- ding the properties we attribute to the object; we end up attributing to it properties *incompatible* with properties we attributed to it earlier. But-- and this is the second feature--despite this change we take the object to have remained *numerically one and the same*. Now, there do not seem to be constraints on our perceptual "change of mind": we can take ourselves to have misperceived ANY (and any number) of the o