Re: Shallow Or Deep Search?

["P.J.Leonard" <P.J.Leonard@xxxxxxxxxx>]

David Fotland wrote:
> 
> The full board evaluation uses the tactician a lot:  to
> evaluate tactical stability of strings, to evaluate some
> connections, to evaluate the control of eye-diagonals.
> 
> Thus the full board evaluation is quite slow.  The tactician is
> pretty fast - I'd guess about 20K nodes per second, but the full board
> evaluator is maybe only 3-5 nodes per second.
> 
> So, I use two different search algorithms.  For tactics, I use
> alpha-beta, depth first, without iterative deepening.  There is
> no fixed depth.  Instead I fix a node count, and allocate the remaining
> nodes among the subtrees at each ply.  I search more cantidate moves near the
> root and fewer cantidates deep in the tree.  This falls into the deep
> search category.  Maximum search depth is 80 ply, and 20-30 ply is typical.

 Do you ever re-apply the full board engine at terminals of a tactical
search ?
For example if your candidate move was suggested for tactical reasons
you could 
examine the terminals of forcing sequences as if they where the seed of
a search.

> For life and death reading I use a different search algorithm that is more
> "best first" in nature.  The evaluation is so slow that the overhead of
> switching around within the tree is negligable.  The tree sizes are small,
> at most a few hundred nodes, so there is no problem with keeping the whole
> tree around.  My thinking here is to guide the search as much as possible
> by things learned during the search.  Usually if you search a few lines,
> you can discover the keys points, and try them next.  Similar to the
> history heuristic used
> in computer chess.  This is not a breadth first search since I search each
> line
> until I get a good live/dead answer.  I have good life and death heuristics
> and
> good move generation heuristics already, so PN search is not a good
> cantidate for
> me since it doesn't use this information to guide the search.

 My version of PN can use ordering information to incremental expand a
node.
This allows heuristically good moves to be explored first. You can also
use heuristics
to assign  the initial proof numbers (a high initial proof number will
discourage the searching of 
a node) but I found incremental expansion of the tree more satisfactory.

 cheers Paul.