Author: Roger D Davis
Date: 16:02:58 12/02/04
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On December 01, 2004 at 17:37:39, Andrei P wrote: >in Livshitz book "Test your chess IQ first challenge", which test human tactical >skills, he gives a table that shows a correlation between % solved and elo >strength. To create the table, the author tested the tactics in the book on >humans with known elo and and then fitted the data into the table (see below). > >% solved elo >100% 2200 >90% 2000 >80% 1800 >70% 1600 >60% 1400 >50% 1200 > >I thought that, in general, one should be able to treat puzzles like players of >a given strength. The stronger the puzzle,the higher its "elo". so one gets >higher elo performance by solving higher rated puzzles etc. But according to >this table, the puzzles do not behave like human players. For example, one could >surmise that the average elo of the puzzles in this "tournament" is 1200 (humans >with 1200 elo solve 50%), so according to fide expactacy, a 1600 player should >score 92% against opposition of 1200, but scores only 70% in the table. > >What is the reason that relation between % solved and elo is different than for >human-human matches? if anybody has references to how puzzles are rated that >would be great. > >Thank you, Andrei Hi Andrei, I suggest you try an empirical approach. Download a bunch of Winboard engines with ratings established by some reputable rating list. Then, give each engine 5 seconds, 10 seconds, 30 seconds to solve each problem. You'll have to play with the time a bit... For example, no engine can solve any problem at 0 seconds, and probably almost all engines can solve all problems at 10 hours. What you want is a time control at which about half the engines pass a puzzle and half fail. There is no reason why the time control has to be the same across all puzzles, but it might things simpler. If you treat puzzles as opponents for engines, then you should be able compute an ELO for each puzzle. Roger
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