Based on the score, comparing it to https://www.sp-cc.de/eas-ratinglist.htm Leorik should be one of the most agressive engines ever without even trying? But I doubt that's really the case. I don't understand how the EAS tool works exactly but I think what it means is that you need to have a wide range of engines that are both stronger and weaker before you can draw meaningful conclusions.
Minimal Chess (simple, open source, C#) - Youtube & Github Leorik (competitive, in active development, C#) - Github & Lichess
lithander wrote: ↑Mon Feb 12, 2024 5:47 pm
Before releasing Leorik 3 I did a mini gauntlet with a few opponents and this is the EAS score when I stuff the PGN in the EAS tool:
Based on the score, comparing it to https://www.sp-cc.de/eas-ratinglist.htm Leorik should be one of the most agressive engines ever without even trying? But I doubt that's really the case. I don't understand how the EAS tool works exactly but I think what it means is that you need to have a wide range of engines that are both stronger and weaker before you can draw meaningful conclusions.
Those results look a bit odd. Leorik sacrificing twice as often as any other opponent and winning way faster on average? And how did PESTO not play a sacrifice even once? The raw data clearly suggests Leorik is really aggressive. Maybe a couple of its opponents are vulnerable to tactical shots? Thanks for the info, it gives me something to think about.
Leorik winning 8% of its games in under 40 moves seems to suggest there were one or two hopeless engines that Leorik crushed over and over again, while the other engines couldn’t enjoy that benefit because they only played Leorik.
Whiskers wrote: ↑Mon Feb 12, 2024 9:55 pm
Leorik winning 8% of its games in under 40 moves seems to suggest there were one or two hopeless engines that Leorik crushed over and over again, while the other engines couldn’t enjoy that benefit because they only played Leorik.
Anchoring the engines to their CCRL ratings shows that the only really hopeless engine was PeSTO. Maybe PeSTO was providing Leorik with all the opportunities to play short, aggressive wins. That's a good theory!
lithander wrote: ↑Mon Feb 12, 2024 5:47 pm
Before releasing Leorik 3 I did a mini gauntlet with a few opponents and this is the EAS score when I stuff the PGN in the EAS tool:
Based on the score, comparing it to https://www.sp-cc.de/eas-ratinglist.htm Leorik should be one of the most agressive engines ever without even trying? But I doubt that's really the case. :roll: I don't understand how the EAS tool works exactly but I think what it means is that you need to have a wide range of engines that are both stronger and weaker before you can draw meaningful conclusions.
So far I have never tried this tool, but it seems obvious it will only show meaningful results in matches or full round tournaments (e.g. not in gauntlets and not in tournaments, where players have a different number of games - provided its calculations are correct anyway).
@ Adam
Thanks for the dev log of your new 'Patricia' - will enjoy your posts about it, as I did and still do with Thomas' Leorik :)
trollwatch:
Talkchess nowadays is a joke - it is full of trolls/idiots/clone lovers/people stuck in the pleistocene > 80% of the posts fall into this category...
I added RFP, LMR, NMP, and history to Patricia; she's now at around 2900 strength already. She also remains more aggressive than the corresponding Willow version:
It's time to work a little bit more on Patricia's aggressiveness. This time around, I plan to retrain my network on "aggressive" data filtered from my Willow dataset at lower LR. This should keep most of the knowledge that the net already has, just slanting it a little bit towards the new positions I'm adding in; I expect this new net to be slightly worse at regular chess, but much better at aggressive chess, which is what I want.
The only problem is that my data is all in binpack format, so I need to write a converter.
Whiskers wrote: ↑Thu Feb 15, 2024 4:26 pm
I added RFP, LMR, NMP, and history to Patricia; she's now at around 2900 strength already. She also remains more aggressive than the corresponding Willow version:
It's time to work a little bit more on Patricia's aggressiveness. This time around, I plan to retrain my network on "aggressive" data filtered from my Willow dataset at lower LR. This should keep most of the knowledge that the net already has, just slanting it a little bit towards the new positions I'm adding in; I expect this new net to be slightly worse at regular chess, but much better at aggressive chess, which is what I want.
The only problem is that my data is all in binpack format, so I need to write a converter.
chesskobra wrote: ↑Thu Feb 15, 2024 10:45 pm
Interesting project, I will be following. Do the position filters work on epd files or pgn files? Do they compile on linux?
They work on text files that contain FEN lines. I did this because I have a lot of Willow data lying around in that format (that I convert to binpacks for nnue training). It would not be very difficult to change it to work with pgns, but I don't see the point for my purposes right now. If demand is high enough I'll generalize the position filter programs and make them easy to build too.
Of course, I am not requesting you to generalise them but I was only curious since I was wondering if such programs could be used to extract interesting positions from game databases for the purpose of human training.
I don't understand how the EAS tool works exactly but I think what it means is that you need to have a wide range of engines that are both stronger and weaker before you can draw meaningful conclusions.
