Computers and Chess

Early Artificial Intelligence (AI) researchers were interested in Chess - it required calculation but it also had an element of creativity and intuition. Programs were soon developed using ideas introduced by Shannon and many others to more efficiently prune the move trees. As computing power increased, these programs became capable of beating the best human players. Deep Blue (using specialised hardware) played the world champion Kasparov in 1996, winning a game but losing the match. In 1997 it won a rematch, though this may have had more to do with Kasparov's approach than an improvement by Deep Blue. Even without specialised hardware programs like Fritz running on standard PCs can complete for first place in national championships (Holland 2000, for example). So chess is an AI success story - one of the few early dreams which have come true.

In a way, however, chess has been an AI disappointment. The above programs tend to have a fairly simple static analysis routine. They gain their power by number-crunching through as many positions as they can. They don't "plan", or "learn" in the way that the AI pioneers had expected to be necessary, and their development hasn't led to ideas that have been of wider use.

But there is another parallel strand of chess program development. Botvinnik (ex-World Champion and an Electrical Engineer) amongst others devoted time trying to give computers an "understanding" (in the human sense) of chess positions. This approach has fallen into neglect - it hasn't produced powerful chess programs - but now with more powerful computers and programming techniques it might be time for a revival. Benefits include

Adding some of these facilities to freely available chess programs as modules would be an interesting project.

See also


Updated: October 2002