Texel tuning for piece values

[Ronald]

With gradient descent a lot of times you will only find a local minimum and not always the global minimum. The values you get may be a local minimum. You may help the tuning proces by starting with values you think should be the optimal values. If you start with the textbook material values and you still end up with the same values then you really have a bug.

[Ferdy]

I understand how texel tuning works for PST, or for other evaluation parameters. But I don't understand how someone can tune piece values this way. Usually in the sample positions (some millions) the numbers of queens will mostly always be the same (1 per color), and the number of pawns will also mostly be the same (+/-1). Only the number of knight/bishop/rook will differ sometimes thanks to some exchange that have been done. But in the millions of positions used, most of them will show the exact same number of pieces on the two side. This way there is no chance to tune piece values I think, the convergence rate would be infinitly small and mini batch gradient or stochastic gradient "sampling" will most alway slead to near 0 gradient for queens, or pawn value.

How some engines were successfull to do so ?

This depends on the training positions you use. There are training positions that have equal material but has differences in positions like one is better in passer but has bad mobility. This has no effect on material tuning.

Try something like the one used by a0. Initially set your default piece to non optimal, p=30, b=n=120,r=300,q=450. Texel is the same but its values are closer to optimal, than those values. Create matches between this version at fast tc using that default values. Save the position and result and use it to train the engine. Use the new values after training and create another matches from this current values and so on. Create matches, save pos, train, update values. Your training may involve only the eval or qsearch . But the matches of games has a search time this would make the result in those games more accurate and is the driving force towards optimal values.

[D Sceviour]

What about this post ? http://talkchess.com/forum3/viewtopic.p ... es#p778420

I have not changed my opinion that imbalance formula are a waste of time. On the contrary, I like how Schooner frequently undertrades for a won endgame. It makes for some dashing tactics. White to move from Schooner-Fritz:

[d]r3r1k1/1p1q3n/1pp2p2/1Pn1p2Q/P1P1P3/2BP2P1/5R1P/5R1K w - - 0 35
RxP! Do not forget that chess engines have to see exchanges such as this very deep on the horizon, so it is not that obvious a position to get into. The full game was posted on this page:

http://talkchess.com/forum3/viewtopic.p ... 20#p777990