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Ray Kurzweil on Computer Chess
« on: 2003-02-04 14:22:37 » |
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[rhinoceros]
An excerpt from an article on computer chess written by Ray Kurzweil's after the Kramnik - Deep Fritz match in Bahrain a few months ago.
http://www.kurzweilai.net/meme/frame.html?main=/articles/art0527.html?m%3D4
Deep Fritz Draws: Are Humans Getting Smarter, or Are Computers Getting Stupider?
<snip>
So what can we say about the software in Deep Fritz? Although chess machines are usually referred to as examples of brute-force calculation, there is one important aspect of these systems that does require qualitative judgment. The combinatorial explosion of possible move-countermove sequences is rather formidable.
In The Age of Intelligent Machines (http://www.kurzweilai.net/meme/frame.html?main=/meme/memelist.html?m%3D12, I estimated that it would take about 40 billion years to make one move if we failed to prune the move-countermove tree and attempted to make a "perfect" move in a typical game (assuming about 30 moves in a typical game and about eight possible moves per play, we have 830 possible move sequences; analyzing one billion of these per second would take 1018 seconds or 40 billion years). I noted that this would not be regulation play, so a practical system needs to continually prune away unpromising lines of play. This requires insight and is essentially a pattern-recognition judgment.
Humans, even world class chess masters, perform the minimax algorithm extremely slowly, generally performing less than one move-countermove analysis per second. So how is it that a chess master can compete at all with computer systems that do this millions of times faster? The answer is that we possess formidable powers of pattern recognition. Pattern recognition incidentally is my principal area of technical interest and expertise, and is, in my view, the primary basis of human intelligence. Thus we perform the task of pruning the tree with great insight.
After the Deep Blue-Kasparov match, I suggested to Murray Campbell, head of IBM's Deep Blue team, that they replace the somewhat ad hoc set of rules they used for this pruning judgment task, and replace it with a well- designed neural net. All of the master games of this century are available on line, so it would be possible to train these neural nets on a considerable corpus of expert decisions.
This approach would combine the natural advantage of machines in terms of computational speed with at least a modest step towards more sophisticated pattern recognition. Campbell liked the idea and we were getting set to convene an advisory group to flesh out the idea when IBM cancelled the project.
It is precisely in this area of applying pattern recognition to the crucial pruning decision that Deep Fritz has improved considerably over Deep Blue. Despite Deep Fritz having available only about 1.3% as much brute force computation, it plays chess at about the same level because of its superior pattern-recognition-based pruning algorithm.
So chess software has made significant gains. Deep Fritz has only slightly more computation available than CMU's Deep Thought, yet is rated almost 400 points higher.
<snip>
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