Author: Jay Scott
Date: 08:54:22 06/23/99
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On June 22, 1999 at 14:32:26, Dave Gomboc wrote: >On June 22, 1999 at 13:17:35, Jay Scott wrote: >>You're suggesting the obvious algorithm, almost exactly what I suggested >>some months ago. > >It predates "some months ago" by a long time. I am sure people thought of it at >least 10 years ago. I mean, almost exactly what I suggested to Dann Corbit the last time he mentioned his unusual updating algorithm. Like I said, it's obvious. So I'm puzzled that chess programs don't implement it! >Overspecified, but it will work fine. Yes, overspecified. The details may be completely different. >>A more intensive novelty-search would find all moves within, say, >>half a pawn of the best move. Just use the "Next Best" feature until >>you've got 'em all. For the Kasparov effect, repeat the novelty search >>on the novelties until you have a whole subtree of analysis ready for >>your next opponent. The new scores float up the tree and may change >>the best move at the original node--the ideal is to discover that the >>novelty that seemed at first to be second-best is actually quite strong. > >Even the second-best ones are fine. As a rule, you only get one game with them >before they're not novelties anymore. As long as it gives the opponent >something to think about and a chance to go wrong, you're ahead. In human chess, when a hot novelty comes up at the top level there's a race to analyze it, to be the first to refute it or to find an improvement. Kasparov, and before him Fischer, showed that deep home analysis can be devastating. Computers can run this race too--but so far they don't. Seeing opening book errors in the recent WCCC, some people are suggesting that computer books should be shallower, because the programs can find stronger moves on their own. But home analysis, when it's possible, is better than spending time to find the moves over the board. So I think offline book learning is an idea whose time is ripe. Chess programmers, go for it! Jay
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