Unknown Workload action
Active : 4 Machines / 68 Threads / 75.73 MNPS
Priority 0
ErenStashdepth-8-fpdiff8.0+0.08LLR: -2.89 (-2.94, 2.94) [0.00, 5.00]
Games: 14910 W: 3803 L: 3858 D: 7249
Ptnml(0-2): 214, 1786, 3487, 1777, 191
more deeper quiet futility pruning
Priority -1
ErenStashdepth-8-fpdiff40.0+0.40LLR: -0.43 (-2.94, 2.94) [0.00, 5.00]
Games: 950 W: 218 L: 231 D: 501
Ptnml(0-2): 8, 128, 217, 113, 9
[SPEC] LTC
Priority -2
MhouppStashthread_votingdiff5.0+0.05LLR: -1.22 (-2.94, 2.94) [0.00, 5.00]
Games: 25390 W: 6038 L: 5984 D: 13368
Ptnml(0-2): 189, 3056, 6167, 3078, 205
Add thread voting to search (Note: impl derived from Stormphrax which is itself ported from Stockfish)
Finished
ErenStashimproving-probcutdiff8.0+0.08LLR: -3.58 (-2.94, 2.94) [0.00, 5.00]
Games: 16088 W: 4071 L: 4150 D: 7867
Ptnml(0-2): 223, 2005, 3658, 1944, 214
apply improving margin to probcut
ErenStashdepth-5-sediff8.0+0.08LLR: -3.00 (-2.94, 2.94) [0.00, 5.00]
Games: 6410 W: 1561 L: 1655 D: 3194
Ptnml(0-2): 84, 810, 1490, 758, 63
shallower SE attempts
ErenStashbetter-razoringdiff8.0+0.08LLR: 3.05 (-2.94, 2.94) [0.00, 5.00]
Games: 13690 W: 3659 L: 3477 D: 6554
Ptnml(0-2): 161, 1592, 3188, 1712, 192
an idea from Halogengine
ErenStashbetter-razoringdiff40.0+0.40LLR: 2.97 (-2.94, 2.94) [0.00, 5.00]
Games: 34204 W: 8355 L: 8112 D: 17737
Ptnml(0-2): 212, 3966, 8504, 4207, 213
an idea from Halogengine
MhouppStashchp_lmr_depthdiff8.0+0.08LLR: -2.97 (-2.94, 2.94) [0.00, 5.00]
Games: 20852 W: 5155 L: 5188 D: 10509
Ptnml(0-2): 259, 2571, 4795, 2546, 255
Use LMR depth for Continuation History Pruning
MhouppStashlmr_cutnode_no_ttmovediff40.0+0.40LLR: -2.96 (-2.94, 2.94) [0.00, 5.00]
Games: 17832 W: 4154 L: 4195 D: 9483
Ptnml(0-2): 115, 2096, 4497, 2131, 77
Increase LMR for expected cutnodes with no TT move
MhouppStashlmr_cutnode_no_ttmovediff8.0+0.08LLR: 3.15 (-2.94, 2.94) [0.00, 5.00]
Games: 37742 W: 9551 L: 9263 D: 18928
Ptnml(0-2): 475, 4450, 8738, 4728, 480
Increase LMR for expected cutnodes with no TT move
RosentWinternet_end_p *diff8.0+0.08LLR: -2.96 (-2.94, 2.94) [-5.00, 0.00]
Games: 20464 W: 5192 L: 5430 D: 9842
Ptnml(0-2): 599, 2484, 4207, 2440, 502
A much more reasonable middle ground.
RosentWinternet_end_p *diff8.0+0.08LLR: -2.98 (-2.94, 2.94) [-5.00, 0.00]
Games: 1216 W: 243 L: 393 D: 580
Ptnml(0-2): 54, 189, 236, 111, 18
Regression testing net training idea.
KierenHalogenspsa_tune_21diff40.0+0.40Tuning 122 Parameters
1501/25000 Iterations
24024/400000 Games Played
MhouppStashnode_timemandiff40.0+0.40LLR: -3.00 (-2.94, 2.94) [0.00, 5.00]
Games: 3628 W: 777 L: 871 D: 1980
Ptnml(0-2): 29, 436, 958, 382, 9
Add node repartition scaling to time management
RosentWinternet_end_p *diff8.0+0.08LLR: 3.08 (-2.94, 2.94) [-5.00, 0.00]
Games: 13636 W: 3293 L: 3219 D: 7124
Ptnml(0-2): 272, 1627, 2966, 1661, 292
Non-regression sanity check.
MhouppStashnode_timemandiff8.0+0.08LLR: -3.04 (-2.94, 2.94) [0.00, 5.00]
Games: 8042 W: 1941 L: 2029 D: 4072
Ptnml(0-2): 81, 1028, 1906, 910, 96
Add node repartition scaling to time management
MhouppStashlmr_less_for_checksdiff40.0+0.40LLR: -2.95 (-2.94, 2.94) [0.00, 5.00]
Games: 20020 W: 4691 L: 4723 D: 10606
Ptnml(0-2): 107, 2377, 5054, 2385, 87
Decrease LMR if the move gives check
RosentWinternet_end_pdiffN=64000Elo: 7.25 +- 13.90 (95%) [N=1000]
Games: 1006 W: 272 L: 251 D: 483
Ptnml(0-2): 19, 118, 213, 129, 24
Sanity test of net training
KierenHalogenr140diff40.0+0.40LLR: -3.00 (-2.94, 2.94) [0.00, 3.00]
Games: 23402 W: 5751 L: 5874 D: 11777
Ptnml(0-2): 58, 2740, 6228, 2617, 58
KierenHalogenr140diff8.0+0.08LLR: -2.96 (-2.94, 2.94) [0.00, 3.00]
Games: 21304 W: 5467 L: 5604 D: 10233
Ptnml(0-2): 179, 2559, 5287, 2474, 153
KierenHalogenr141diff40.0+0.40LLR: -2.96 (-2.94, 2.94) [0.00, 3.00]
Games: 16686 W: 4066 L: 4202 D: 8418
Ptnml(0-2): 43, 2006, 4373, 1886, 35
VshcheIgelttfixdiff10.0+0.10LLR: -1.04 (-2.94, 2.94) [0.00, 3.00]
Games: 8730 W: 2238 L: 2284 D: 4208
Ptnml(0-2): 68, 1081, 2115, 1031, 70
3.6.14: improve tt store algo
RosentWinternet_502_24x64 *diff8.0+0.08LLR: -2.96 (-2.94, 2.94) [0.00, 5.00]
Games: 6688 W: 1605 L: 1709 D: 3374
Ptnml(0-2): 168, 856, 1382, 788, 150
Warmup Stable Decay seems to fit the training pipeline better than the previous linear scheduler based on metrics. Does this hold in self play?
KierenHalogenr141diff8.0+0.08LLR: -2.96 (-2.94, 2.94) [0.00, 3.00]
Games: 17808 W: 4497 L: 4643 D: 8668
Ptnml(0-2): 153, 2180, 4360, 2082, 129
KierenHalogenr141diffN=40000Elo: 1.53 +- 2.08 (95%) [N=40000]
Games: 40038 W: 11527 L: 11351 D: 17160
Ptnml(0-2): 706, 4651, 9046, 4993, 623
VshcheIgelttfixdiff60.0+0.60LLR: 0.00 (-2.94, 2.94) [0.00, 3.00]
Games: 0 W: 0 L: 0 D: 0
Ptnml(0-2): 0, 0, 0, 0, 0
3.6.14: improve tt store algo
KierenHalogenr140diffN=40000Elo: 4.78 +- 2.11 (95%) [N=40000]
Games: 40232 W: 11932 L: 11379 D: 16921
Ptnml(0-2): 715, 4570, 9052, 5005, 774
RosentWinternet_502_24x64 *diffN=40000Elo: 2.86 +- 7.28 (95%) [N=4000]
Games: 4006 W: 1111 L: 1078 D: 1817
Ptnml(0-2): 102, 478, 824, 483, 116
Get an understanding of how far apart the based increased size net is compared to the current version. Fixed nodes in this case as system load would otherwise distort results.