This patch increases LMRdepth threshold for futility pruning at parent nodes so it can apply more often.
With radical change to evaluation approach it seems that search is really far from optimal state, especially it parts that use static evaluation of position.
passed STC
https://tests.stockfishchess.org/tests/view/5f2da75661e3b6af64881fd0
LLR: 2.93 (-2.94,2.94) {-0.50,1.50}
Total: 8744 W: 1305 L: 1156 D: 6283
Ptnml(0-2): 75, 789, 2500, 928, 80
passed LTC
https://tests.stockfishchess.org/tests/view/5f2dcb2a61e3b6af64881ff3
LLR: 2.98 (-2.94,2.94) {0.25,1.75}
Total: 17728 W: 1256 L: 1117 D: 15355
Ptnml(0-2): 22, 961, 6774, 1070, 37
Bench: 4067325
Allow any pawn in front of a minor piece to replace the pawn protection
requirement for outposts.
+-------+ +-------+
| . . o | | o . . | o Their pawns
| . o x | | o . . | x Our pawns
| o N . | | x o B | N,B New (reachable) outpost
| . . . | | . _ . | _ Reachable square behind a pawn
+-------+ +-------+
N outpost B reaches
outpost
We want outposts to be secured by pawns against major pieces. If
a minor is shielded by any pawn from above, it is rarely at the same
time protected by our pawn attacks from below. However, the pawn shield
in itself offers some degree of protection.
A pawn shield will now suffice to replace the pawn protection for the
outpost (and reachable outpost) bonus.
This effect stacks with the existing "minor behind pawn" bonus.
STC
https://tests.stockfishchess.org/tests/view/5f2bcd14b3ebe5cbfee85b2c
LLR: 2.94 (-2.94,2.94) {-0.50,1.50}
Total: 27248 W: 5353 L: 5119 D: 16776
Ptnml(0-2): 462, 3174, 6185, 3274, 529
LTC
https://tests.stockfishchess.org/tests/view/5f2bfef5b3ebe5cbfee85b5a
LLR: 2.96 (-2.94,2.94) {0.25,1.75}
Total: 99432 W: 12580 L: 12130 D: 74722
Ptnml(0-2): 696, 8903, 30049, 9391, 677
Closes#2935
Bench: 4143673
This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish.
Both the NNUE and the classical evaluations are available, and can be used to
assign a value to a position that is later used in alpha-beta (PVS) search to find the
best move. The classical evaluation computes this value as a function of various chess
concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation
computes this value with a neural network based on basic inputs. The network is optimized
and trained on the evalutions of millions of positions at moderate search depth.
The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward.
It can be evaluated efficiently on CPUs, and exploits the fact that only parts
of the neural network need to be updated after a typical chess move.
[The nodchip repository](https://github.com/nodchip/Stockfish) provides additional
tools to train and develop the NNUE networks.
This patch is the result of contributions of various authors, from various communities,
including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather,
rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler,
dorzechowski, and vondele.
This new evaluation needed various changes to fishtest and the corresponding infrastructure,
for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged.
The first networks have been provided by gekkehenker and sergiovieri, with the latter
net (nn-97f742aaefcd.nnue) being the current default.
The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option,
provided the `EvalFile` option points the the network file (depending on the GUI, with full path).
The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on
the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest:
60000 @ 10+0.1 th 1
https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c
ELO: 92.77 +-2.1 (95%) LOS: 100.0%
Total: 60000 W: 24193 L: 8543 D: 27264
Ptnml(0-2): 609, 3850, 9708, 10948, 4885
40000 @ 20+0.2 th 8
https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58
ELO: 89.47 +-2.0 (95%) LOS: 100.0%
Total: 40000 W: 12756 L: 2677 D: 24567
Ptnml(0-2): 74, 1583, 8550, 7776, 2017
At the same time, the impact on the classical evaluation remains minimal, causing no significant
regression:
sprt @ 10+0.1 th 1
https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b
LLR: 2.94 (-2.94,2.94) {-6.00,-4.00}
Total: 34936 W: 6502 L: 6825 D: 21609
Ptnml(0-2): 571, 4082, 8434, 3861, 520
sprt @ 60+0.6 th 1
https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d
LLR: 2.93 (-2.94,2.94) {-6.00,-4.00}
Total: 10088 W: 1232 L: 1265 D: 7591
Ptnml(0-2): 49, 914, 3170, 843, 68
The needed networks can be found at https://tests.stockfishchess.org/nns
It is recommended to use the default one as indicated by the `EvalFile` UCI option.
Guidelines for testing new nets can be found at
https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests
Integration has been discussed in various issues:
https://github.com/official-stockfish/Stockfish/issues/2823https://github.com/official-stockfish/Stockfish/issues/2728
The integration branch will be closed after the merge:
https://github.com/official-stockfish/Stockfish/pull/2825https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip
closes https://github.com/official-stockfish/Stockfish/pull/2912
This will be an exciting time for computer chess, looking forward to seeing the evolution of
this approach.
Bench: 4746616
