Harpists spend 90 percent of their lives tuning their harps and 10 percent playing out of tune.
My computer just finished a second tuning run trying to optimize the search control parameters in my engine. This time it run for another 364 hours. I optimized the parameter set a bit, removed dead parameters (parameters belonging to a feature that the first run decided to disable) and added a few new ones. I also lowered the learning rate and modified the fitness function a bit.
Due to the lower learning rate the second run converged slower but as also fewer mutations occurred the final entropy after 1.100 generations was about the same.
|Convergence comparison between both runs|
|Average Population Search Depth for midgame positions (move 10 - 25)|
The convergence towards an aggressive set also shows in the search depth the winner engine reaches in the final round of the knock out tournament in each generation.
|evol-2 tournament winner depth incl. trend line|
|Futility Pruning Safety Margins|
|ELO development (engine base version = 0)|
The outcome of the 2nd run seems a bit stronger. But considering the error bar they are really close together.
Rank Name Elo + - games score oppo. draws
1 evol-v2.1100 70 6 6 10004 54% 43 42%
2 evol-v1.1100 62 6 6 10004 52% 49 41%
3 iCE 0.4 v1604 0 7 7 6004 40% 66 40%
Maybe it is just coincidence or it is an indication how much the strength of my engine with the current code base can be improved just be tuning search parameters.
I will have to think about it and decide how to progress from here. Maybe I perform a third run to test my hypothesis.