Wasp 4.5 is released today. I estimate it to be about 50 Elo stronger than Wasp 4.0.
Many thanks to Frank Quisinsky for hosting Wasp on his website. Here is the link:
https://www.amateurschach.de/download/wasp_450.zip
Most of the strength increase comes from re-writing the evaluation function to allow for much faster parameter tuning. The eval uses conventional features such as material, piece-square tables, mobility, and king-safety etc... Most of the eval terms are similar or identical to those in Wasp 4.0, but a few have been modified, for example a second set of PST's is now used when the kings are on opposite wings. Tuning is now done in a similar fashion to back-propogation for neural networks rather than the gradient-descent method that was previously used. Tuning was done on a set of 28M positions randomly selected from about 2M games between Wasp and engines of similar strength. I use Andrew Grant's method of doing a shallow (only depth 2) search and storing the quiet position at the end of the PV along with the game result. All evaluation parameters are initialized to what I feel are "reasonable" values, then the parameters are tuned with about 40 passes through a 28M position EPD file, which takes around an hour using 1 thread. During tuning, for each position in the data set the evaluation is done and a counter is incremented for each feature that is used in computing the eval. The error between the eval (converted to win-probabilty) and the game result (0.0/0.5/1.0 for loss/draw/win) is computed and each pertinent term is tweaked by a small amount in the direction to reduce error.
John
Wasp 4.5 Released
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- Full name: John Stanback
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Re: Wasp 4.5 Released
jstanback wrote: ↑Fri Jan 01, 2021 7:37 pm Wasp 4.5 is released today. I estimate it to be about 50 Elo stronger than Wasp 4.0.
Many thanks to Frank Quisinsky for hosting Wasp on his website. Here is the link:
https://www.amateurschach.de/download/wasp_450.zip
Most of the strength increase comes from re-writing the evaluation function to allow for much faster parameter tuning. The eval uses conventional features such as material, piece-square tables, mobility, and king-safety etc... Most of the eval terms are similar or identical to those in Wasp 4.0, but a few have been modified, for example a second set of PST's is now used when the kings are on opposite wings. Tuning is now done in a similar fashion to back-propogation for neural networks rather than the gradient-descent method that was previously used. Tuning was done on a set of 28M positions randomly selected from about 2M games between Wasp and engines of similar strength. I use Andrew Grant's method of doing a shallow (only depth 2) search and storing the quiet position at the end of the PV along with the game result. All evaluation parameters are initialized to what I feel are "reasonable" values, then the parameters are tuned with about 40 passes through a 28M position EPD file, which takes around an hour using 1 thread. During tuning, for each position in the data set the evaluation is done and a counter is incremented for each feature that is used in computing the eval. The error between the eval (converted to win-probabilty) and the game result (0.0/0.5/1.0 for loss/draw/win) is computed and each pertinent term is tweaked by a small amount in the direction to reduce error.
John
Thanks John Stanback......We Love the Wasp Engines!! AR
ps Thanks Frank Q.!!
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Re: Wasp 4.5 Released
Great news, John.
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Re: Wasp 4.5 Released
this is the gradient-descent. the neural network also uses gradient-descent. backprop propagate the error back for hidden layer(s) and.
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Re: Wasp 4.5 Released
Thank you, John! Nice news. What is the "proper" version number: 4.5 or 4.50 ?jstanback wrote: ↑Fri Jan 01, 2021 7:37 pm Wasp 4.5 is released today. I estimate it to be about 50 Elo stronger than Wasp 4.0.
Many thanks to Frank Quisinsky for hosting Wasp on his website. Here is the link:
https://www.amateurschach.de/download/wasp_450.zip
Incredibly fast systems miscount incredibly fast.
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Re: Wasp 4.5 Released
Thanks John!
"Good decisions come from experience, and experience comes from bad decisions."
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Ted Summers
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Ted Summers
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Re: Wasp 4.5 Released
Many thanks John. How do you use the config file. I used example_config with UCI_Elo = 1200 and set ConfigFilePath=./example_config in the Shredder 12 GUI. But it seems to search much more deeply than I expect for 1200 elo and gets depth around 8 ply.
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Re: Wasp 4.5 Released
Any chance to get a macOS binary? The last one was Wasp 3.75 I think.