EMR based on Null Move threat

[jwes]

I think this subverts the entire idea of null move. The reason that you can reduce the null move compared to the normal search depth is based on the assumption that the normal search will start with some delaying tactic that postpones any threat 2 ply. What you are doing here is confirm that you indeed have a delaying tactic by trading some valuable piece, and which thus would push the threat that made null move fail low over the horizon, and then reduce anyway rather than extending the horizon (copmpared to the null move search).

The reason that you can reduce null move is because you are giving the opponent two moves in a row to see how much damage can be done. If that damage does not bring score < beta then a beta-cut can be made. Null move is not safe as it brings the horizon closer. However, the extra depth gained in the search more than makes up for that.

If null move fails to cause a cut that means that there is an immediate threat found at the reduced depth of search. As long as you search the "solution" move to the same depth the horizon is the same as in the null move search. I chose a reduction of two additional ply as that is the minimum r_value in null move searching. So the horizon for the "solution" search is often further away than it was in the null move search.

Null move can also fail to cause a cut if the current position is not that good. I would think you would at least want to ensure the current position is well above beta before doing something.

[Michael Sherwin]

Good idea. Thanks

[PK]

I have tested the following variation of your idea:

if null move has been tried and qs score is greater than beta, then increase late move reduction depth by one.

It tested ok-ish, 50,5% after 4000 games, and there is some scope for improvement.

Then I understood what my code represents: it is a special case of ProbCut-turned-reduction.

[Michael Sherwin]

I have tested the following variation of your idea:

if null move has been tried and qs score is greater than beta, then increase late move reduction depth by one.

It tested ok-ish, 50,5% after 4000 games, and there is some scope for improvement.

Then I understood what my code represents: it is a special case of ProbCut-turned-reduction.

An idea is like a gold mine. You dig around in it and maybe a nugget or two of gold worth keeping might be found.