what is the rating advantage of hash in fixed depth search

[Uri Blass]

I believe that hash should help at fixed depth search because programs may find the best move earlier thanks to hash cutoff(for example in fine70 programs can find Kb1 earlier than depth 26 thanks to hash cutoff).

I wonder if somebody investigated if using hash for pruning improve the rating at fixed depth search and what is the size of the advantage per depth.

Uri

[Aleks Peshkov]

Earlier or later fixed depth search will reach horizon. There is almost no difference (except random factor of transposition table instability), if your do not consider time.

[Uri Blass]

Earlier or later fixed depth search will reach horizon. There is almost no difference (except random factor of transposition table instability), if your do not consider time.

tranposition table instability is not a random effect and I think that if hash is used correctly hash should help not only to reach the same depth faster but also help to get better result in the same depth in part of the cases.

Uri

[Aleks Peshkov]

Instability is a difference between hashed result and research of the same node again is fundamental because of random difference in move ordering (killer/history tables moment states are "random" factors) between two separate searches of a single position at different time. Different move ordering may lead to different cut moves and different principal variation.

[Uri Blass]

Instability is a difference between hashed result and research of the same node again is fundamental because of random difference in move ordering (killer/history tables moment states are "random" factors) between two separate searches of a single position at different time. Different move ordering may lead to different cut moves and different principal variation.

Different move ordering may lead to different cut moves but the point is that cutoff may lead also to finding the right move at smaller depth.

Uri