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Artificial Intelligence and the Human Mind

Just in case you missed this article where the Great Garry Kasparov opines at length about chess and computers:


  1. I may as well paste in comments I made at the Chess Mind blog and in Mig's ChessNinja blog:

    From my standpoint as a computer-science researcher, Kasparov is spot-on. The only nit I can pick is I believe the # of legal positions is closer to Shannon's original estimate 10^43 than 10^40. I wholly agree with his statement that competitive chess should be viewed scientifically as an arena for understanding human thinking. I hope my ongoing quantitative work will make good on that.

    Incidentally, this work is also supporting basically all his assertions about the nature and evolution of chess in his My Great Predecessors series.


    Let me add something specifically about this paragraph of Kasparov's review:

    "Like so much else in our technology-rich and innovation-poor modern world, chess computing has fallen prey to incrementalism and the demands of the market. Brute-force programs play the best chess, so why bother with anything else? Why waste time and money experimenting with new and innovative ideas when we already know what works? Such thinking should horrify anyone worthy of the name of scientist, but it seems, tragically, to be the norm. Our best minds have gone into financial engineering instead of real engineering, with catastrophic results for both sectors."

    This paragraph mixes a technical statement about brute-force search as optimal for playing chess with several social statements. I agree with the last sentence, but can shed a different light on the ones before it by raising a scientific point of my professional field, which is computational complexity theory. There is actually a clash of two increasing strands of evidence. One is that for many classes of computational problems---including finding a winning line in a chess position when one exists, and hundreds of vital practical problems---there may exist no algorithm that is applicable in all cases and improves substantially on brute-force search. Indeed, we have adopted the Russian word perebor to mean brute-force search in this technical context. The other is that for some cases of these problems, often many cases or separate sets of cases, there are "idea-based" algorithms that work well on those cases. David S. Johnson and Richard M. Karp (an avid chess follower, USCF 1800-ish) are leaders of the latter strand.

    If the former strand of evidence proves out, it will "tragically" be the norm in my field that brute-force-search is optimal, except for tuning, as a scientific fact. My field would then impute that this scientific fact is felt in all walks of life. Of course, my field has not proved anything remotely like this yet. And "tuning" is not a trivial issue---even in chess, Rybka is believed by some to employ novel ideas about quantifying near-term mobility and generating evaluations. Ultimately ideas have to compete, and in chess the grounds of competition are brutally clear...

  2. And what I wrote at ChessNinja:


    I disagree with those disagreeing with Garry; I think his points are very well taken. I "J'adoube" his comments slightly and say more about "brute force" here [referencing the above two comments in "The Chess Mind"]. Otherwise, I basically agree with "ra" and "Computer Scientist" in this thread [at ChessNinja].

    If I recall correctly that it was Bill Hartston, he described to me in the early 1980s his efforts at a "Human Chess Knowledge" approach to computer chess---while acknowledging that optimized search might beat him out. The fact that sophisticated algorithmics and chess evaluation functions go into today's engines still leaves GK's basic point intact. The point by "ra" that a depth plateau might bring "HCK" back is interesting, but Vas Rajlich posted before Rybka 3 that extra ply were still bringing him almost-undiminished returns.