Author: Uri Blass
Date: 02:32:06 12/24/02
Go up one level in this thread
On December 24, 2002 at 04:16:11, John Lowe wrote: >On December 23, 2002 at 20:23:04, Robert Hyatt wrote: > >>On December 23, 2002 at 19:21:57, Uri Blass wrote: >> >>>On December 23, 2002 at 18:31:03, Dieter Buerssner wrote: >>> >>>>On December 23, 2002 at 18:08:15, Martin Bauer wrote: >>>> >>>>>Hello, >>>>> >>>>>i have a queastion about move ordering. There are many sources with move >>>>>ordering heuristics like killer heuristic, history and so on... >>>>> >>>>>But I found no description _how_ to program the move ordering in an _efficient_ >>>>>way. In my own enginge I use an integer value together with the move and put it >>>>>on the move stack. Moves that should be searched first, become a high value and >>>>>the less important moves a low one. Then there is a function named >>>>>"NextBestMove" that that looks for the highest value at the actual searchdepth >>>>>on the movestack. Therefore it must look at all possible moves in the actual >>>>>position. When the best move is found, the value is set to -Matescore, so it can >>>>>not get the best move the next time the function is called. >>>> >>>>This is the normal way to do it, I think. Instead of giving a "marker score", to >>>>not search the move again, you could shift the move to the start or to the end >>>>of the array, and remember the new bounds (incrementing a pointer may be enough >>>>for this). This will save a few CPU cycles. It is essentially the inner loop of >>>>a normal selection sort. >>>> >>>>>This algorithm must have a look at all possible moves in the position at the >>>>>actual depth, even if the frist 10 best moves are searched. This look not >>>>>efficient to me, because it is an O(n) algorithm in reading the best move and >>>>>O(1) in storing the best move. >>>> >>>>I think, there is no practical better way. Sorting the whole move list can >>>>easily be done faster (especially, when it has some considerable length, so not >>>>just relpy to check). But often, the work will be done for nothing, because one >>>>move will be enough for a cutoff. I experimented a bit with the following idea: >>>>Try to guess, when we expect a fail high node: use the selection sort method >>>>above. Whe expecting a fail low node, do a qsort (the Standard C-language qsort >>>>would probably be a bit slow for this, because of all the calls to the compare >>>>function, I had written my own). But, I really could not measure any performance >>>>increase, so I gave up on the idea. It just made the code bigger ... >>> >>>If you expect a fail low move you can simply not care about order of moves. >>>Latest movei does not continue to sort the moves if the first 10 moves did not >>>give a fail high(I do not know if 10 is the best number but the gain that I may >>>get from changing it is small because movei is not a fast searcher). >>> >>>Uri >> >>I've done this in crafty for many years. I try the hash move, the good capture >>moves, the killer moves (2), and then if the first 4 history moves don't produce >>a fail high, I just take the remaining moves in the order they were generated. >> >>saves time. > >I have understood good capture, killer and history but could you expand "hash >move" a little. (Terra incognita for me) hash move is a move that you remember from the hash tables and caused a fail high in the same position in previous search. Uri
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