To generate quality games by string engines, what is a good balance between average depth and computation time?
I'm trying to find the balance to find good time controls
Thanks
Moderator: Ras
That was a nice paper. So H1.5a is around 2900 compared to some top human players with average rating of around 2800 that participated in candidates 2013.Peperoni wrote: ↑Fri Nov 06, 2020 9:59 pm Hello Dann,
Thanks for your answer.
Yes, my idea is not to compete with those
I would like to create interesting games at a minimum of 3200 ELO that could be useful for chess players to find interesting novelties in openings.
I found this paper that makes a correspondance between ELO and depth : https://pdfs.semanticscholar.org/047f/6 ... f58666.pdf
Even if it is an approximation, I was wondering if using strong engines at depth 25/30 for example would create games interesting enough to find nice novelties that humans can explore.
I am looking for a good ratio quality/quantity. My hardware is "good", 3970X processors and dual 2070 Super![]()
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Score of H1.5a_d20 vs Sf12_d16: 1 - 11 - 5 [0.206] 17
... H1.5a_d20 playing White: 0 - 7 - 2 [0.111] 9
... H1.5a_d20 playing Black: 1 - 4 - 3 [0.313] 8
... White vs Black: 4 - 8 - 5 [0.382] 17
Elo difference: -234.5 +/- 179.3, LOS: 0.2 %, DrawRatio: 29.4 %
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Score of Sf12_d18 vs Sf12_d16: 18 - 1 - 41 [0.642] 60
... Sf12_d18 playing White: 10 - 1 - 19 [0.650] 30
... Sf12_d18 playing Black: 8 - 0 - 22 [0.633] 30
... White vs Black: 10 - 9 - 41 [0.508] 60
Elo difference: 101.2 +/- 46.8, LOS: 100.0 %, DrawRatio: 68.3 %
I don't know which of them generates more games. Just try both and see which one is faster. But with more threads, it will reach the required depth faster.
Core, but you can use threads as well as this is fixed-depth games anyway.
That is the depth of the data generated by Bojun Guo for his opening project.