Engines tournament July 2020:
Time per game: 3 minutes
Processor: Intel i7-4771, 4 threads for each engine
Hashtable size: 1024 MBs
Permanent brain (ponder): OFF (Yes, I know I always tell to set it ON, but for one time I wanted to kick in all the processor strength
Interface used: Fritz 17 with 6 MEN Syzygy tablebases.
Games here
I had to take a snapshot of the table with something else because Fritz 17 messed it up.
This is a surprising tournament because of two factors:
1. the amazing performance of BrainLearn
2. the very scarce performance of Raubfisch
Stockfish Polyglot did a mediocre performance, placing itself between CorChess and Brainfish.
If we take a look at the table we can see that BrainLearn started to win while going forth with the games: this could mean that its learning algorithms are really functioning, the most of wins got against Raubfisch.
This last one instead made a very scarce performance, maybe because of a bug...
I want to point out that ALL the engines were used with their default values except for 4 threads for each of them.
Since I only host the strongest chess programs I will suspend the hosting of Raubfisch until the issue is fixed and I will reintroduce BrainLearn between my ranks.
My compliments go to Thomas Zipproth, author of Brainfish.
Time per game: 3 minutes
Processor: Intel i7-4771, 4 threads for each engine
Hashtable size: 1024 MBs
Permanent brain (ponder): OFF (Yes, I know I always tell to set it ON, but for one time I wanted to kick in all the processor strength
Interface used: Fritz 17 with 6 MEN Syzygy tablebases.
Games here
I had to take a snapshot of the table with something else because Fritz 17 messed it up.
This is a surprising tournament because of two factors:
1. the amazing performance of BrainLearn
2. the very scarce performance of Raubfisch
Stockfish Polyglot did a mediocre performance, placing itself between CorChess and Brainfish.
If we take a look at the table we can see that BrainLearn started to win while going forth with the games: this could mean that its learning algorithms are really functioning, the most of wins got against Raubfisch.
This last one instead made a very scarce performance, maybe because of a bug...
I want to point out that ALL the engines were used with their default values except for 4 threads for each of them.
Since I only host the strongest chess programs I will suspend the hosting of Raubfisch until the issue is fixed and I will reintroduce BrainLearn between my ranks.
My compliments go to Thomas Zipproth, author of Brainfish.