Date: Wed 17 Feb 1988 21:19-PST From: AIList Moderator Kenneth Laws Reply-To: AIList@KL.SRI.COM Us-Mail: SRI Int., 333 Ravenswood Ave., Menlo Park, CA 94025 Phone: (415) 859-6467 Subject: AIList V6 #35 - Genetics, Fuzzy Logic, Nanotechnology, Greenblat To: AIList@KL.SRI.COM Status: RO AIList Digest Thursday, 18 Feb 1988 Volume 6 : Issue 35 Today's Topics: References - Genetic Algorithms & Self-Organizing Systems, AI Tools - Fuzzy Logic vs. Probability Theory, Nanotechnology - Altering Individual Atoms, Biography - Richard Greenblat ---------------------------------------------------------------------- Date: 15 Feb 88 18:22:11 GMT From: g451252772ea@deneb.ucdavis.edu (0040;0000001899;0;327;142;) Subject: Re: becoming literate with genetic algorithms The references, generally at good libraries, that I know of for GAs: Introductory: Holland, J., et al. INDUCTION. 1986, MIT Press. The book is a coherent whole, not a collection of separately authored papers - and reads very well by any standard. Most of it discusses human induction, but the main model introduced early on is Holland's. And the human material is fascinating in its own right, only partly because of the lucid presentation. The description of Holland's GA is complete, and an alternative system, PI, is also presented. This is a more familiar symbol-based production system, in LISP. Holland, J. "Genetic Algorithms and Adaptation", in O. Selfridge, et al, ADAPTIVE CONTROL OF ILL-DEFINED SYSTEMS. 1984, Plenum Press, NY. This is a discrete chapter, in which an overview of GA is provided. Almost every main theme is touched on. Davis, L. GENETIC ALGORITHMS AND SIMULATED ANNEALING. 1987, Morgan Kauffman Pub, Los Altos, CA. A collection of research papers by Holland's colleagues, mostly (his INDUCTION chapters are reproduced here also). A good variety of current work, and again very lucid as technical/research writing goes (by contrast, the Neural net literature is hopeless). Topics include a study of the TSP; parallel implementation of the CFS-C simulation library for GA on the Connection Machine (nice!); Axlerod's study of GA in round-robins of the iterated Prisoner's dilemma; a somewhat vague but very suggestive study on designing a mapping from 'an East Asian language' onto a usable keyboard, using a GA; some formal tests of 'hard' problems for GAs; and another suggestive paper (for me) on producing long action sequences with GA by means of 'hierarchical credit allocation' (this problem has parallels in the animal-behavior literature I'm familiar with). Holland, J. ADAPTION IN NATURAL AND ARTIFICIAL SYSTEMS. 1975, U. Michigan Press. The definitive foundation, marred only by a generous use of formal notation (not insensibly, but offputting nonetheless). The main conceptual addition since this has been the interpretive change in INDUCTION, I think. The GA community has held two conferences, last summer and in '86. The proceedings are available from Lawrence Erlbaum Assoc., 365 Broadway, Hillsdale, NJ 07642. My copy is on order ("Proc. Second International Conf. on GA and their applications", held at Cambridge, MA, July 28-81, 1987). And the various dissertations Holland has supervised are worth perusing via U.Microfilm copies at $25 each. For relating GA to NNets, I'll hazard to volunteer Richard Belew's name. He responded to an earlier posting I made and stated an interest in what commonalities there might be. He teaches at UCSD: rik@sdcsvax.ucsd.edu. Oh yes: as the _very best_ intro article to GA, I recommend the final issue of Science 86, for July, I think. Too bad that mag died. Hopefully helpfully (let me know what else you find- I've been teaching this material to budding animal behaviorists!) - Ron Goldthwaite / UC Davis, Psychology and Animal Behavior 'Economics is a branch of ethics, pretending to be a science; ethology is a science, pretending relevance to ethics.' ------------------------------ Date: 14 Feb 88 15:31:54 GMT From: trwrb!aero!venera.isi.edu!smoliar@ucbvax.Berkeley.EDU (Stephen Smoliar) Subject: Re: becoming literate with genetic algorithms In article <9430@shemp.CS.UCLA.EDU> jason@CS.UCLA.EDU () writes: >John Holland was here recently giving talks on genetic algorithms. I found >the >concept rather intriguing. After hearing his lectures, I realized I needed to >do some introductory reading on the subject to fully appreciate its potential. > The best source would be the book entitled INDUCTION, which Holland wrote with Holyoak, Nisbett, and Thagard. Most of the material from the talk is in Section 4.1 (I think). The preceding material leading up to the major argument is very well written, as is the subsequent discussion. ------------------------------ Date: 16 Feb 88 11:16:27 GMT From: Gilbert Cockton Reply-to: Gilbert Cockton Subject: Re: self organizing systems In article <8801291421.aa28769@ARDEC-AC4.ARDEC.ARPA> pbeck@ARDEC.ARPA (Peter Beck, LCWSL) writes: > >Is this a generally accepted proposition, ie, that complex constituent >elements can "NOT" form self organizing systems?? Broadly speaking, social theories are often opposed across a co-operation vs. conflict continuum. Theories in the Marxian tradition stress conflict as a fundamental dynamic of society. Theories in the functionalist tradition stress adaptation towards universal ends (e.g. Talcott-Parsons). Look to Marxian theories (e.g post/neo/vanilla -structuralism) for evidence of non-self-organisation. Look to functionalist ones for evidence of dormitory consensus. NB Rednecks! - 'Marxian' is a scholarly term, 'Marxist' is both a scholarly and a political term. Marx claimed he wasn't a Marxist! It is thus safe to follow up these ideas without the risk of brainwashing yourself into running off to Cuba/Nicaragua :-) -- Gilbert Cockton, Scottish HCI Centre, Heriot-Watt University, Chambers St., Edinburgh, EH1 1HX. JANET: gilbert@uk.ac.hw.hci ARPA: gilbert%hci.hw.ac.uk@cs.ucl.ac.uk UUCP: ..{backbone}!mcvax!ukc!hci!gilbert ------------------------------ Date: Mon, 15 Feb 88 20:46:33 PST From: golden@frodo.STANFORD.EDU (Richard Golden) Subject: FUZZY LOGIC VS. PROBABILITY THEORY I am not an expert in Fuzzy Logic or Probability Theory but I have examined the literature regarding the foundations of Probability Theory and the derivation of these foundations from basic principles of deductive logic. The basic theoretical result is that selecting a "most probable" conclusion for a given set of data is the ONLY RATIONAL selection one can make in an environment characterized by uncertainty. (Rational selection in this case meaning consistency with the classic deductive/symbolic logic - boolean algebra.) Thus, one could argue that if one constrains the class of possible inductive logics to be consistent with the laws of deductive logic then Probability Theory is the MOST GENERAL type of inductive logic. The reference from which these arguments are based is given by Cox (1946). Probability Frequency and reasonable expectation. American Journal of Statistical Physics, 14, 1-13. The argument is based upon the following hypotheses: (i) The belief of the event B given A may be represented by a real-valued function F(B,A). (ii) F(~B,A) may be computed from F(B,A) (iii) F(C and B,A) may be computed from F(C,B and A) and F(B,A) Note this assumption's similarity to Bayes Rule but the multiplicative property is not assumed. (iv) Assumptions (i), (ii), and (iii) must be consistent with the laws of Boolean Algebra (i.e., deductive/symbolic logic). >From these assumptions one can prove that F(B,A) must be equivalent to the conditional probability of B given A. That is, F(B,A) must lie between a maximum and minimum value (say 1 and 0) and the sum of all possible values for B for a particular value of A must equal the maximum value (1). Note that we are taking the subjectivist view of probability theory and we are NOT interpreting the probability of an event as the limiting value of the relative frequency of an event. To my knowledge, the axioms of Fuzzy Logic can not be derived from consistency conditions generated from the deductive logic so I conclude that Fuzzy Logic is not appropriate for inferencing. Any comments?!!! Richard Golden Psychology Department Stanford University Stanford, CA 94305 GOLDEN@PSYCH.STANFORD.EDU Cc: ------------------------------ Date: Mon, 15 Feb 1988 18:31 EST From: MINSKY%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU Subject: AIList V6 #27 - Nanotechnology Dolata's reamrks about nanoscopic chemistry missed the point, so far as I can see, in arguing that because it is a scanning microscope it is not involved with individual molecules but is more like regular volume chemistry. However, the molecular rearrangement was not accomplished by a conventional bulk effect. Instead, it was accomplished by a sub-microsecond pulse applied during the scan so that it occurred while the needle was over a particular molecule. The next step, of course, is to try to make a particular modification at a particular site on the molecule. Much more will be done in the area soon, I'm sure, because the techniques seem quite accessible. But I see no reason to denigrate the technique because it uses scanning. Simply think of scanning as examining, and possibly modifying, large numbers of points is sequence. What could be better? The trouble with traditional chemistry is, in fact, that it is constrained to do the same thing to everything, in parallel. ------------------------------ Date: 14 Feb 88 08:28 From: minow%thundr.DEC@decwrl.dec.com (Martin Minow THUNDR::MINOW ML3-5/U26 223-9922) Subject: Article on Richard Greenblat AIList readers might enjoy this article from the Boston Globe, Feb. 7, 1988. ZORCHED OUT: A COMPUTER HACKER'S TALE by Alex Beam, Boston Globe staff Richard Greenblatt: Single-minded, unkempt, prolific, and canonical MIT hacker who went into night phase so often that he zorched his academic career. The hacker's hacker. - HACKERS by Steven Levy. CAMBRIDGE -- "Lights On!" Greenblatt yells, pushing through the door of MIT's Model Railroad Club. "That's just in case anybody's sleeping under the layout." He explains to a visitor. "They might pick up a shock or something." Happily, no one is sleeping underneath the thousand feet of handmade track that may be the world's most sophisticated model railway. The last person to fall asleep under the layout was probably Greenblatt, who spent so much tinkering - "hacking" - with the railroad's switching system, and with his other favorite toy, computers, that he flunked out of MIT in his sophomore year. Greenblatt, now 44, has gone on to bigger things. After a long career as senior researcher at MIT's Artificial Intelligence Lab, he helped found Lisp Machine Inc., one of the first artificial intelligence startups. Now he is president of Cambridge-based GigaMOS, which purchased LMI's assets after it went broke last year. But scratching the surface of Richard Greenblatt, AI entrepreneur, one quickly finds traces of 17-year-old Ricky Greenblatt, the soda-pop swilling science whiz who arrived at MIT as a bewildered freshman from Columbia, MO, in 1963. Greenblatt still drops in on the railroad club from time to time, and exudes boyish enthusiasm when demonstrating "the famous Greenblatt track cleaning machine," a cleverly-engineered locomotive that spins an abrasive grinding wheel over the nickel-silver track. He sheepishly explains that he is "out of phase" on a particular day, because he spent the previous night hacking away on a computer. And even though he has cleaned up his presentation - friends say he bathed so rarely as an undergraduate that they had to ambush him with air freshener - Greenblatt still acts like an absent-minded computer genius. Pallid-skinned from long hours of computer work, he trundles around Cambridge in rumpled work pants and a plaid shirt, with a digital calculator watch protruding from his breast pocket and a cellular phone slung across his shoulder. Although he has earned plenty of money in his computer ventures, he still rents a room in the same house in Belmont where he has lived for 20 years. Why not buy a house: "It's too much trouble," Greenblatt says. "You have to pay taxes, mow the lawn. I don't want to bother." "Ricky lives in a world of his own, dominated by his own genius," says Andy Miller, who briefly roomed with Greenblatt at MIT. "We never saw him when he lived with us. The Sun meant absolutely nothing to him - it happened to rise and fall in a way that wasn't in synch with his schedule." After two semesters on the Dean's List at MIT, Greenblatt threw in with the small band of electronics fanatics hanging around the Model Railroad Club. Synchronizing the model railroad's switching system - its circuits can control five trains chugging across the vast layout, and set the 200 switches so no crashes occur - turned out to be a lot like programming the early computers that were making their first appearance in MIT labs. (It also resembled another electronic gimmick called "phone hacking," or fooling the phone system into placing free long-distance calls, which resulted in suspension of several of Greenblatt's friends.) Greenblatt and his friends often spent the daylight hours working on the railroad, and then migrated to a neighboring lab to stay up all night next to the PDP-1, DIGITAL EQUIPMENT CORP.'s first computer. Fueled by the Railroad Club's private Coca-Cola machine, Greenblatt and his fellow hackers "wrapped around" day into night, working for 30 hours at a stretch to solve thorney problems, either with the railway or the computer. "To a large extent, our group wasn't interested in the normal social events around the institute," explains fellow hacker Alan Kotok, now a corporate consulting engineer at Digital. "The railroad club was like a fraternity. There were people you could talk to day or night about things of common interest. Although no one asked him to, Greenblatt wrote a high-level language computer program for the PDP-1, so the club's timetable system could be stored on the new computer. Unfortunately, the young programmer's deepening involvement in computer hacking doomed his academic career. "I sort of zorched out on classes," Greenblatt admits. During one of his 30-hour work blasts, Greenblatt slept through a final exam, and had to leave MIT. Of course, MIT didn't get where it is today by turning away computer talent. After a brief sojourn on Route 128, Greenblatt landed a job as a programmer at the Artificial Intelligence Lab, and stayed for 20 years. Greenblatt's fame grew and grew. He and a co-worker wrote ITS, and early minicomputer time-sharing program that is still in use today. He was one of the early programmers to work in LISP, the high-level language that has become the key building block for artificial intelligence. "He would attack problems with great vigor," remembers Donald Eastlake, another railroad club alumnus. "Everybody was smart, but the people who really excelled were smart and tenacious. He was one of the primary examples of that." An accomplished chess player, Greenblatt wrote MacHack, a chess program for a later DIGITAL mini, the PDP-6. The program scored an important victory for AI boosters when it defeated a prominent critic of artificial intelligence who insisted that a computer would never play chess well enough to beat a 10-year old. The program later became a member of the American Chess Federation and the Massachusetts State Chess Association. When Greenblatt later did graduate work at MIT, administrators hinted that if he submitted his chess program as a doctoral thesis, he might be awarded a degree. "I never really got around to it," Greenblatt confesses. "It just didn't seem that important." ------------------------------ End of AIList Digest ********************