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NYT Story On Go Programs And AI

mykej writes: "The NYT (registration required, blah blah) has a story on Go, the hardest game for computers to play. From the article: 'Programmers working on Go see it as more accurate than chess in reflecting the ineffable ways in which the human mind works. The challenge of programming a computer to mimic that process goes to the core of artificial intelligence, which involves the study of learning and decision-making, strategic thinking, knowledge representation, pattern recognition and, perhaps most intriguingly, intuition.' There are a few throwaway lines about Nash from 'A Beautiful Mind,' although they don't mention the game he invented after getting frustrated with the inconsistencies of go."

9 of 244 comments (clear)

  1. Kasparov and IBM by natpoor · · Score: 5, Interesting

    The NYTimes is not exactly correct about the Kasparov/Deep Blue match. The IBM programmers studied Kasparov's playing style intensely, and programmed Deep Blue to not just play chess but more specifically play and beat Kasparov, which is a slightly different thing from "playing chess." (Granted the machine could still beat almost anyone, but maybe not other masters with a different playing style.) Kasparov, on the other hand, was not allowed to study how Deep Blue might play at all. I also recall that Kasparov became a bit unhinged early on. So yes, Deep Blue did beat Kasparov, but the problem for it was not just "play chess" it was "beat Kasparov."

    1. Re:Kasparov and IBM by God!+Awful · · Score: 5, Interesting

      At one point, I was trying to improve my chess game by studying the game archive that comes with ChessMaster. After only a few weeks of practice, I discovered that I could predict each move (in the midgame) with uncanny accuracy (80%). However, my chess game didn't actually improve. All I had done was train my brain to be a fuzzy logic analyzer for predicting Kasparov moves against high quality opponents. The basic strategy fails miserably against amateur players (who tend to be less subtle in their attack). One of the ways Kasparov came back to beat Deep Blue in their original match was to suddenly switch strategies to something the machine was not expecting.

      -a

  2. History on Go by RobinH · · Score: 5, Informative

    Try this site.

    It also has instructions on how to teach Go, if you're interested.

    --
    "I have never let my schooling interfere with my education." - Mark Twain
  3. Good article about Go and servers by Antity · · Score: 5, Interesting

    There was a really good article about Go on kuro5hin maybe three weeks ago. In fact, it caused me to start playing again and it still is much fun. :-)

    Just try it. There are lots of free Go servers online. I prefer the KGS server. All you need is to download the client or just play it online in your browser with others (Java required). There are usually ~100 people online in the English room (yes, chat included).

    It's a wonderful game.

    --
    42. Easy. What is 32 + 8 + 2?
  4. Re:A tidbit about Go by flipflapflopflup · · Score: 5, Informative
    Whilst I'm personally a Go fan, not a chess fan, I don't think I agree with your arguments.

    >Go in its pure form is played on a 19x19 board as supposed to an 8x8 board
    So? What has the size of a board got to do with it? In chess you can move pieces around, in GO you cannot.

    >Chess's famous plays, games and styles have all been archived, whereas Go's strategies are largely abstract and can only be learned by repeated play
    Not really true. There are masses of games available as .sgf files that you can study to your hearts content. THere are many clasic moves to make in certain positions, etc.

    >The game only begins to take structure after 30 to 50 moves.
    Again, not really. THere are masses of standard opening patterns (fuseki), and also many standardised plays (joseki) that can go on during a game. A whole lot goes on in the first 20 - 30 moves to shape the rest of the game.

    Go is a great game, it doesn't need imbalanced comparisons with chess to prove it, you just need to play the game a while to realise that. Maybe you should try.

  5. It will take a general-purpose AI to play go by Bob+Hearn · · Score: 5, Insightful

    I love go (I'm a 2 kyu player), and I'm an AI researcher. But I don't work on go-playing programs. Much as I'd like to, I don't think it would be a productive activity for me.

    I think that the minute you start to write a game-playing program, you're trapped by the very natural structures you have to use to make the program even play a legal game. You can't help but start to use minimax search. With go, you add modules for life & death evaluation, influence generation functions, the list goes on and on.

    But all these things are just hard-coded approximations of some of the ways people think about go when they play, ripped out of their essential representational context. Real people have rich conceptual networks linking all of these skills together, which multiplies their power enormously. Give a beginning human player a perfect black-box life and death evaluator, like go programs ideally have, and he will never become a strong player. Only by solving life and death problems yourself (to take just one example) can you integrate that kind of knowledge into your total go knowledge. I maintain that this integration is essential.

    Will computers ever beat people at go? Sure. But I'll bet the first program to do so will be a general-purpose near-human level AI, that thinks of board positions in terms of physical metaphors. It will have a rich mental landscape.

    Bob Hearn

  6. Why Go Programming is Difficult by mechner · · Score: 5, Informative

    A more in-depth article on go programming, from the point of view of a programmer and a player, originally published in The Sciences: http://mechner.com/david/compgo/ Click on "All Systems Go".

  7. Other information about Go - Links-a-plenty by gatekeep · · Score: 5, Informative

    For those of you interested in learning more about Go, here's some links to resources I've found helpful since starting to play 3 weeks ago.

    k5 had an article about go which is what initially piqued my interest and got me started in the game.

    Kiseido Go Server is my favorite place to play online, and very newbie friendly.

    Some great introductions are available from Kiseido The Interactive Way to Go and Tel's Go Notes

    Uligo and Goproblems.com are great places for learning how to play in common situations.

    If you prefer a phyiscal board and stones check out Samarkand and Kiseido

    Also, anyone in the Chicago area should check out the Evanston Go Club

    A word of caution, if you decide to learn go, expect to lose most of your first 50-100 games. It's a long road, but once you start making progress, you'll grow quickly. I know I sure have. Anyone who's up for a game look for 'jjarmoc' on KGS.

  8. Standing on the shoulders of giants by dsr9996 · · Score: 5, Insightful
    Hello Bob,

    I respect what you are saying here and understand your reasons for not working on a go-playing program yourself, but I would challenge you with this: Even though you will probably not be the person to write the go ai program that is "near-human level", the person who does eventually write it (X number of years/decades in the future) will most definitely only be able to do it because he learned from people who came before him and attempted the endeavor. In short, it takes Newton to formulate the basic laws for physics and the calculus before Einstein can go further and discover relativity and quantum physics. And as Newton said, the only reason he could accomplish what he did was because he "stood on the shoulders of giants" that had come before him.

    I am sure that this is not a new idea to you, but I present it again because I think it is very valid. We are at a very primitive state when it comes to computer ai, as anyone who has done any ai knows, both because of our lack of understanding of how our own intelligence/consciousness works, and because of our lack of good programming tools that allow us to work at a high abstraction of thought (i.e. most of the code we write is very tedious, and even though it is necesssary for our ai programs, it has little to do with actual ai). It is similar to knowing that you need a modern race-car when oil refineries, engines, and smelting have not even been invented yet. It is up to us to create those go-carts, pardon the pun, and start exploring how we might create a smelter, looking forward to the day when the infrastructure will be in place for others to continue the progress.

    I know what you mean when you say that when you begin work on an ai problem like go, you are immediately trapped into things you have been taught, common procedures that you know others have used for similar types of problems, etc. However, this does not mean that you cannot be the one to think up the next innovation with respect to ai, taking the next step in creating a "rich mental landscape" that will lead to the integration you believe is essential to true ai.

    I am quite positive that you are more knowledgeable about ai than me, since I have only dabbled in it here and there, but I hope you take my encouragement in the spirit I have intended to give it.

    Peace to you,
    Devin