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Subject: Re: Move Ordering

Author: Dave Gomboc

Date: 02:46:02 12/24/02

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On December 24, 2002 at 05:41:50, John Lowe wrote:

>On December 24, 2002 at 05:32:06, Uri Blass wrote:
>
>>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
>
>That's what I thought but why "try" again - have some parameters changed?

Yes, you're searching one ply deeper this time. :-)

Dave



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