LAWS@SRI-AI.ARPA (05/21/85)
From: AIList Moderator Kenneth Laws <AIList-REQUEST@SRI-AI> AIList Digest Tuesday, 21 May 1985 Volume 3 : Issue 67 Today's Topics: Query - Cooking Knowledge, Theory - Classes of Turing Machines, Games - Computer Cheating, Humor - Qualitative Calculator, Seminars - Constraint-Interpreting Reference (MIT) & Exceptions in Data/Knowledge Bases (LBL) ---------------------------------------------------------------------- Date: Mon, 20 May 85 14:41:54 -0200 From: mcvax!vu44!klipper!biep@seismo.ARPA Subject: Cooking Knowledge Doing research on collaboration between robot systems, we need to implement knowledge about cooking. I've heard that long, long ago, a group in San Diego worked on that, and that some Mrs. Cordier in Paris has done research in that field. Does anyone have more information on these, or on other projects using cooking knowledge, or does someone have any ideas about the subject which might be useful? Thanks, Biep. {seismo|decvax|philabs|garfield|okstate}!mcvax!vu44!klipper!biep ------------------------------ Date: Mon, 20 May 85 15:06 CDT From: Patrick_Duff <pduff%ti-eg.csnet@csnet-relay.arpa> Subject: RE: a "new" turing thesis > From: Lydia Defilippo <DEFILIPPO@CMU-CS-C.ARPA> > Subject: Seminar - A New "Turing" Thesis (CMU) > > .... Turing machines are computational devices with unbounded resources. > First, we adapt Turing's thesis to the case when only devices with bounded > resources are considered. When I studied Turing machines in an AI course I took back in college, this had already been done. Here is a summary of the four types of Turing Machines (with various bounds on the available resources), from my class notes [if you have any corrections or additions, please send them to me]: TYPE 3 TURING MACHINE: Description: 1) Tape has finite length; 2) Control unit has one read head and no write heads; 3) Read head is initially positioned at beginning of tape; 4) Read head cannot be moved backwards; 5) Control unit is deterministic; 6) Control unit has finite memory. Remarks: 1) Recognizes exactly all regular languages; 2) Making control unit non-deterministic does not increase power; 3) Equivalent to a finite-state automaton; 4) Able to decide whether a number is odd, compute the sum of two numbers, or decide whether a number is divisible by 3, for instance. TYPE 2 TURING MACHINE: Description: 1) Tape has finite length; 2) Control unit has one read head and no write heads; 3) Read head is initially positioned at beginning of tape; 4) Read head cannot be moved backwards; 5) Control unit is deterministic; 6) Control unit has finite memory. 7) Control unit has a push-down stack. Remarks: 1) More powerful than TYPE 3; 2) Recognizes exactly all context free languages; 3) Making control unit non-deterministic does not increase power. 4) Ability to read any position in push-down stack would make it more powerful; 5) Letting read head move both ways adds power; 6) Letting head read and write adds power--more powerful than even without the push-down stack; 7) If a second push-down stack is added, it can do anything a TYPE 0 can do; 8) Using a single counter instead of a push-down stack is more powerful than TYPE 3 but less powerful than TYPE 2 [could check for an arbitrary string of symbols on tape or see if parentheses are balanced, for instance]. TYPE 1 TURING MACHINE: Description: 1) Tape has finite length; 2) Control unit has one read/write head; 3) Read/write head is initially positioned at beginning of tape; 4) Read/write head can be moved both forwards and backwards; 5) Control unit is deterministic; 6) Control unit has finite memory. Remarks: 1) Recognizes context sensitive languages; 2) Also called a linear bounded automata; 3) Adding multiple tapes does not increase power; 4) It is not known whether a non-deterministic control unit increases power. TYPE 0 TURING MACHINE: Description: 1) Tape has infinite length; 2) Control unit has one read/write head; 3) Read/write head is initially positioned somewhere on tape; 4) Read/write head can be moved both forwards and backwards; 5) Control unit is deterministic; 6) Control unit has finite memory. Remarks: 1) Adding multiple tapes does not increase power; 2) Adding multiple read/write heads does not increase power; 3) Adding push-down stack does not increase power; 4) Non-deterministic control unit does not increase power; 5) Infinite memory control unit does not increase power; 6) Able to determine whether a number is prime or whether a program has infinite loops, for instance; 7) Claimed to be "an adequate and complete model of processes that can be carried out mechanically (effective processes)" [Church-Turing thesis]. regards, Patrick Patrick S. Duff, ***CR 5621*** pduff.ti-eg@csnet-relay 5049 Walker Dr. #91103 214/480-1659 (work) The Colony, TX 75056-1120 214/370-5363 (home) (a suburb of Dallas, TX) ------------------------------ Date: Tue, 21 May 85 00:46 EDT From: Henry Lieberman <Henry@OZ> Subject: Computers cheat at chess? The chess columnist of the Boston Globe wrote an article claiming that computer programs cheat in chess tournaments! He had two arguments for this: * Tournament rules forbid the players to use an extra board to move pieces while considering their moves during the game. He argued that tree searching of moves in computer programs constitutes using an extra board. * Tournament rules forbid the players to consult books during the game. Most programs rely on a book to play openings. These arguments seemed silly to me at first, but on reflection, I think he might have a point, especially with the second point about book openings. It might be worthwhile to try human-computer chess tournaments with relaxed rules that, for example, permit the human to consult a book of openings, or even better, the same on-line data base of openings that the program uses. ------------------------------ Date: Thu, 16 May 85 18:01:50 edt From: Walter Hamscher <hamscher at mit-htvax> Subject: Revolting Seminar - Qualitative Calculator [Forwarded from the MIT bboard by SASW@MIT-MC.] DATE: Friday, 17 May TIME: 12 NOON PLACE: 8th FLOOR PLAYROOM HOST: Michael Kashket QUALITATIVE CALCULATORS IN CLINICAL DECISION MAKING (-: Tex Tuftsman :-) The classical approach to decision analysis in medicine has been based on constructing decision trees, giving numerical weights to outcomes, and banging away at the keys of an ordinary 16-key calculator to choose between appropriate therapies. Some of the weaknesses in this approach can be avoided by using a QUALITATIVE CALCULATOR (c) from Ronco. Envision yourself with a QUALITATIVE CALCULATOR (c) -- A QUALITATIVE CALCULATOR especially designed for Naive Physicists. Comes with [+], [-], and [0] keys, plus a Clear key and a DeClear key. Was $20.99, marked down to [+]. But wait -- There's more! Qual before [0] tonight and get a free State Map for your locality. Operators are standing by! Don't miss this landmark value! ------------------------------ Date: Sun, 19 May 85 18:02 EDT From: jcma@MIT-MC.ARPA Subject: Seminar - Constraint-Interpreting Reference (MIT) AI REVOLVING SEMINAR John Mallery (JCMa@MIT-MC) "Constraint-Interpreting Reference" Tuesday, May 21, 1985 at 4pm 8th Floor Playroom, AI Laboratory, MIT This talk will discuss the theory of reference used in the Relatus Natural Language System, an AI program developed at the MIT AI Laboratory in collaboration with Gavan Duffy. Relatus parses sentences and uses a reference system to incrementally construct a semantic model. The reference system matches graphs and creates (interns) graph structure in a semantic network. The separation of the constraint interpreter from specific constraints describing the matching problem yields various benefits. For instance: * Matching speed is independent of database size, normally faster than linear in the size of the smallest accessible set of potential referents. * A powerful and extensible constraint language provides the ability to describe an infinite number of matchers, each tuned to recognize and prefer specific structures. In addition to the theoretical ideas, some practical uses of the implemented reference system will also be discussed: * It is regularly used in intersentential reference, finding references to previously interned descriptions in new sentences. Relatus can presently parse and reference a 10-page text (250 sentences) in under 10 minutes while running on a Symbolics 3600 (1536K real memory). * It is regularly used to answer literal and explicit questions. The approach to question answering depends on both the reference system and a procedure which is actually the inverse of reference. Semantic inversion builds constraint descriptions from the graph structure previously created by the reference system. ------------------------------ Date: Mon, 20 May 85 13:32:05 pdt From: (Frank Olken [csam]) olken@lbl-csam Subject: Seminar - Exceptions in Data/Knowledge Bases (LBL) CSRD Colloquium Lawrence Berkeley Laboratory ********************************************************** Living with Exceptions in Data/Knowledge Bases ********************************************************** Alexander Borgida Department of Computer Science Rutgers University The ``schema'' of a large database is usually used to vali- date the data being entered and to help set up efficient access structures. Because the real world is irregular, unpredictable and evolves, we contend that useful data management systems, including large ``knowledge bases,'' must be tolerant of deviations from the constraints imposed by the schema, including type and semantic integrity con- straints. We therefore examine the problems involved in accommodating exceptions to constraints, and propose a solu- tion based on the concept of exception handling in Program- ming Languages. This technique can also be used to deal with problems such as null values and estimates, and in addition has good Software Engineering properties. We con- clude by discussing the formal logic of assertions with exceptions, and hint at the utility of exceptions in data- base re-design through learning. Wednesday, May 22, 1985, 2:00pm - 4:00pm Bldg. 50D, Room 116 - Conference Room For further information, call Harry Wong at (415) 486-6884. Dept. of Computer Science Research; LBL; One Cyclotron Road; Berkeley, CA 94720. ------------------------------ End of AIList Digest ********************