Author: Russell Reagan
Date: 15:17:09 05/15/03
I would like to know how to test whether or not a forward pruning method is reliable. I have one idea to test when and if a method is reliable, and I'd like to know if it's a good idea or not, and also what other methods might be used to test the reliability of forward pruning methods. My idea requires a collection of games, and two versions of a program. One version would have forward pruning turned off, and the other would have it turned on. You would feed each version of the program the same game, and let each do a search on the initial position to the same fixed depth. If both versions report the same move and score, and the version using forward pruning had a lower time to depth, then the forward pruning is reliable (so far). If the version using forward pruning reported different results, then the forward pruning method is not reliable for this type of position. You make the next move in the game, and repeat the search and compare the results for each position in the game. Then you repeat the process for each game. When I think about testing the reliability of null-move using this method, I think the test would do well. I would expect the test to tell us that in most positions, null-move is reliable, and I would expect it to fail for some endgame positions, and so this test would tell us that null-move was good forward pruning, but to turn it off in the endgame (or detect zugzwang, or however you choose to guard against it). I haven't had time to test this though, since I just thought of it and I'm not at home. I am basing all of this on the assumption that the strength forward pruning provides is not that it finds better moves at the same depth, but that it finishes searching a particular depth in a shorter amount of time, allowing the search to go deeper, which is where the added strength comes from. Is this correct? Comments, please...
This page took 0 seconds to execute
Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.