Author: Ernst A. Heinz
Date: 14:51:13 12/31/99
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Hi Gian-Carlo, >a) where does the quiescent search fit in all this ? Should I just >assume that using a quiescent search is equal to statically evaluating >the position ? I.e. are 'horizon nodes' the ones at the end of the >standard search or those at the end of the quiescent search ? Horizon nodes are the end nodes of the standard search (remaining depth = 0). >I am >already using futility pruning in the quiescent search and I don't >understand how this relates to the kind of futility pruning that's >described by Heinz. They seem indentical to me, except that, well, >mine is done in the qsearch and what Heinz describes looks like doing >it in the standard search. Right, all the different flavours of futility pruning are conceptually quite similar. But the effect of applying futility pruning in the quiescence search as opposed to the main search is quite different because the quiescence search as such is already highly selective. Please also note that normal futility pruning at frontier nodes with a remaining depth = 1 and extended futility pruning at pre-frontier nodes with a remaining depth = 2 are two different flavours of futility pruning in the main search. >b) I understand that just storing the values into the transposition table is >deadly (e.g. having to research after a fail-low would yield garbage), and >this is mentioned in the paper, but how should this optimally be handled then ? Just treat the selective score as a lower bound. Because you did not search some moves at all, the real score might actually be better. =Ernst= P.S. "Scalable Search in Computer Chess" now available at MKP online http://www.mkp.com/books_catalog/3-52805-732-7.asp :-) Visit http://supertech.lcs.mit.edu/~heinz/node1.html for more information about the book.
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