Author: Dann Corbit
Date: 16:27:14 12/28/05
Go up one level in this thread
This is Scorpio data, calculated at a shallow depth of 6 plies in the search.
piece_v[pawns]
(parameter value, solution ratio)
(50,0.501575)
(65,0.513065)
(80,0.517576)
(95,0.522342)
(110,0.528726)
(125,0.530258)
(140,0.526258)
(155,0.531024)
(170,0.527194)
(185,0.522087)
y=-3.49912e-006*x*x +0.000969375*x + 0.462914
depth = 6 parm 0 = 138.517199 (best) with std of 0.001994
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 146.758600
Resetting pawn value to 100 for standardization
piece_v[knights]
(parameter value, solution ratio)
(148,0.485658)
(192.4,0.500128)
(236.8,0.514086)
(281.2,0.523874)
(325.6,0.521661)
(370,0.488382)
(414.4,0.453996)
(458.8,0.417142)
(503.2,0.393821)
(547.6,0.377309)
y=-1.80485e-006*x*x +0.000921447*x + 0.394803
depth = 6 parm 1 = 255.269692 (best) with std of 0.014954
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 268.234846
piece_v[bishops]
(parameter value, solution ratio)
(172.5,0.428973)
(224.25,0.4757)
(276,0.518768)
(327.75,0.526768)
(379.5,0.513576)
(431.25,0.500979)
(483,0.491957)
(534.75,0.47919)
(586.5,0.473913)
(638.25,0.469231)
y=-1.16533e-006*x*x +0.00094888*x + 0.320498
depth = 6 parm 2 = 407.128512 (best) with std of 0.018537
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 367.439256
piece_v[rooks]
(parameter value, solution ratio)
(254,0.503788)
(330.2,0.511363)
(406.4,0.518512)
(482.6,0.518342)
(558.8,0.517576)
(635,0.515618)
(711.2,0.511788)
(787.4,0.510597)
(863.6,0.50532)
(939.8,0.503873)
y=-1.12826e-007*x*x +0.000126521*x + 0.481761
depth = 6 parm 3 = 560.690000 (best) with std of 0.002611
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 483.545000
piece_v[queens]
(parameter value, solution ratio)
(589.5,0.50915)
(766.35,0.516129)
(943.2,0.518938)
(1120.05,0.517916)
(1296.9,0.518768)
(1473.75,0.519363)
(1650.6,0.519023)
(1827.45,0.519193)
(2004.3,0.519278)
(2181.15,0.519193)
y=-7.33948e-009*x*x +2.43662e-005*x + 0.499919
depth = 6 parm 4 = 1659.939270 (best) with std of 0.001691
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 1566.844635
knight_mobility
(parameter value, solution ratio)
(5,0.510256)
(6.5,0.514682)
(8,0.519448)
(9.5,0.52064)
(11,0.519704)
(12.5,0.520981)
(14,0.515959)
(15.5,0.513831)
(17,0.512469)
(18.5,0.506341)
y=-0.000255771*x*x +0.00564058*x + 0.489214
depth = 6 parm 5 = 11.026639 (best) with std of 0.001395
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 11.763319
bishop_mobility
(parameter value, solution ratio)
(3,0.525577)
(3.9,0.525577)
(4.8,0.523364)
(5.7,0.522768)
(6.6,0.519704)
(7.5,0.514086)
(8.4,0.517236)
(9.3,0.511192)
(10.2,0.508128)
(11.1,0.504383)
y=-0.000199012*x*x +0.000139754*x + 0.527438
depth = 6 parm 6 = 0.351120 (best) with std of 0.001654
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 1.675560
rook_mobility
(parameter value, solution ratio)
(1.5,0.517916)
(1.95,0.517916)
(2.4,0.517576)
(2.85,0.517576)
(3.3,0.51698)
(3.75,0.51698)
(4.2,0.518938)
(4.65,0.518938)
(5.1,0.515703)
(5.55,0.515703)
y=-0.000241999*x*x +0.00137596*x + 0.515984
depth = 6 parm 7 = 2.842895 (best) with std of 0.001092
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 3.521447
queen_mobility
(parameter value, solution ratio)
(0.5,0.519363)
(0.65,0.519363)
(0.8,0.519363)
(0.95,0.519363)
(1.1,0.51698)
(1.25,0.51698)
(1.4,0.51698)
(1.55,0.51698)
(1.7,0.51698)
(1.85,0.51698)
y=0.00160484*x*x +-0.00608233*x + 0.522567
depth = 6 parm 8 = 1.895000 (WORST) with std of 0.000658
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 0.500000
knight_outpost list multiplier
(parameter value, solution ratio)
(2,0.518342)
(2.6,0.516129)
(3.2,0.520129)
(3.8,0.520129)
(4.4,0.518768)
(5,0.520981)
(5.6,0.520044)
(6.2,0.517746)
(6.8,0.51332)
(7.4,0.514767)
y=-0.000629576*x*x +0.00529385*x + 0.508932
depth = 6 parm 9 = 4.204296 (best) with std of 0.001692
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 4.602148
qr_on_7thrank list multiplier
(parameter value, solution ratio)
(1,0.52047)
(1.3,0.521321)
(1.6,0.519278)
(1.9,0.517746)
(2.2,0.518938)
(2.5,0.518682)
(2.8,0.519363)
(3.1,0.520044)
(3.4,0.519448)
(3.7,0.519023)
y=0.000730774*x*x +-0.00379228*x + 0.523765
depth = 6 parm 10 = 2.594706 (WORST) with std of 0.000897
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 1.300000
rook_on_hopen list multiplier
(parameter value, solution ratio)
(4,0.520214)
(5.2,0.522598)
(6.4,0.524726)
(7.6,0.52081)
(8.8,0.520385)
(10,0.518172)
(11.2,0.514682)
(12.4,0.51332)
(13.6,0.512044)
(14.8,0.507277)
y=-0.000169708*x*x +0.00183729*x + 0.517164
depth = 6 parm 11 = 5.413087 (best) with std of 0.001504
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 5.906544
dobled_penalty list multiplier
(parameter value, solution ratio)
(2,0.519278)
(2.6,0.518768)
(3.2,0.518768)
(3.8,0.519874)
(4.4,0.518853)
(5,0.517831)
(5.6,0.519023)
(6.2,0.518427)
(6.8,0.518002)
(7.4,0.517491)
y=-6.80622e-005*x*x +0.000369829*x + 0.518599
depth = 6 parm 12 = 2.716842 (best) with std of 0.000548
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 3.258421
isolated_penalty list multiplier
(parameter value, solution ratio)
(4,0.515278)
(5.2,0.514427)
(6.4,0.519619)
(7.6,0.522427)
(8.8,0.517916)
(10,0.520555)
(11.2,0.517831)
(12.4,0.514682)
(13.6,0.513916)
(14.8,0.513916)
y=-0.000202843*x*x +0.00355253*x + 0.503996
depth = 6 parm 13 = 8.756821 (best) with std of 0.002114
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 8.178411
weak_penalty list multiplier
(parameter value, solution ratio)
(2,0.516044)
(2.6,0.518172)
(3.2,0.519534)
(3.8,0.518853)
(4.4,0.519534)
(5,0.518087)
(5.6,0.519959)
(6.2,0.522172)
(6.8,0.52081)
(7.4,0.519959)
y=-0.000154036*x*x +0.0021426*x + 0.513102
depth = 6 parm 14 = 6.954884 (best) with std of 0.001140
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 6.577442
side_bonus list multiplier
(parameter value, solution ratio)
(2,0.521747)
(2.6,0.521747)
(3.2,0.521491)
(3.8,0.521491)
(4.4,0.520725)
(5,0.52081)
(5.6,0.52081)
(6.2,0.519108)
(6.8,0.518427)
(7.4,0.518512)
y=-0.000123587*x*x +0.000492842*x + 0.521268
depth = 6 parm 15 = 1.993913 (best) with std of 0.000408
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 1.996957
passed_bonus list multiplier
(parameter value, solution ratio)
(6,0.522938)
(7.8,0.523108)
(9.6,0.52081)
(11.4,0.520129)
(13.2,0.522087)
(15,0.52081)
(16.8,0.520981)
(18.6,0.521066)
(20.4,0.518512)
(22.2,0.518768)
y=-3.88074e-006*x*x +-0.000116673*x + 0.523441
depth = 6 parm 16 = -15.032308 (best) with std of 0.001041
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at -3.616154
bishop_pair_1
(parameter value, solution ratio)
(15,0.515533)
(19.5,0.515533)
(24,0.515448)
(28.5,0.515363)
(33,0.515193)
(37.5,0.515278)
(42,0.515278)
(46.5,0.515278)
(51,0.515448)
(55.5,0.515278)
y=4.29867e-007*x*x +-3.55786e-005*x + 0.516011
depth = 6 parm 17 = 41.383333 (WORST) with std of 0.000079
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 15.000000
bishop_pair_2
(parameter value, solution ratio)
(15,0.51698)
(19.5,0.515703)
(24,0.514767)
(28.5,0.515533)
(33,0.515618)
(37.5,0.515278)
(42,0.515193)
(46.5,0.515533)
(51,0.515193)
(55.5,0.514597)
y=9.71181e-007*x*x +-9.88455e-005*x + 0.517555
depth = 6 parm 18 = 50.889344 (WORST) with std of 0.000542
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 15.000000
bishop_pair_3
(parameter value, solution ratio)
(10,0.515874)
(13,0.515108)
(16,0.517065)
(19,0.516725)
(22,0.515533)
(25,0.513746)
(28,0.514257)
(31,0.513235)
(34,0.514171)
(37,0.513831)
y=-1.50453e-006*x*x +-3.69256e-005*x + 0.516765
depth = 6 parm 19 = -12.271429 (best) with std of 0.000991
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 1.864286
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-35,0.514086)
(-31,0.514086)
(-27,0.514086)
(-23,0.514086)
(-19,0.514086)
(-15,0.514086)
(-11,0.514086)
(-7,0.514086)
(-3,0.514086)
(1,0.514086)
depth = 6 badfit parm 20
Using default value of -15.000000
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-38,0.513235)
(-32.4,0.513746)
(-26.8,0.514171)
(-21.2,0.513831)
(-15.6,0.514512)
(-10,0.514086)
(-4.4,0.513746)
(1.2,0.514427)
(6.8,0.514171)
(12.4,0.514427)
y=-4.72908e-007*x*x +3.36875e-006*x + 0.514278
depth = 6 parm 21 = 3.561739 (best) with std of 0.000313
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at -6.019130
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-41,0.513065)
(-33.8,0.512724)
(-26.6,0.51298)
(-19.4,0.514257)
(-12.2,0.513746)
(-5,0.513576)
(2.2,0.514342)
(9.4,0.513831)
(16.6,0.514086)
(23.8,0.514086)
y=-3.91806e-007*x*x +1.26766e-005*x + 0.513975
depth = 6 parm 22 = 16.177143 (best) with std of 0.000394
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 9.188571
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-44,0.511873)
(-35.2,0.511703)
(-26.4,0.511363)
(-17.6,0.512299)
(-8.8,0.512214)
(0,0.513831)
(8.8,0.512639)
(17.6,0.51315)
(26.4,0.512554)
(35.2,0.513235)
y=-2.12324e-007*x*x +1.86479e-005*x + 0.512708
depth = 6 parm 23 = 43.913725 (best) with std of 0.000581
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 21.956863
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-47,0.510937)
(-36.6,0.510852)
(-26.2,0.511703)
(-15.8,0.511703)
(-5.4,0.51315)
(5,0.512639)
(15.4,0.513916)
(25.8,0.513576)
(36.2,0.51315)
(46.6,0.512724)
y=-5.36539e-007*x*x +2.75614e-005*x + 0.512919
depth = 6 parm 24 = 25.684444 (best) with std of 0.000507
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 20.542222
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-50,0.511618)
(-38,0.512299)
(-26,0.511618)
(-14,0.512895)
(-2,0.512554)
(10,0.513661)
(22,0.514512)
(34,0.515533)
(46,0.515789)
(58,0.515278)
y=8.73167e-008*x*x +4.11705e-005*x + 0.513306
depth = 6 parm 25 = -235.753846 (WORST) with std of 0.000586
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 46.000000
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-53,0.499957)
(-39.4,0.50549)
(-25.8,0.509831)
(-12.2,0.515448)
(1.4,0.515278)
(15,0.515789)
(28.6,0.518257)
(42.2,0.515789)
(55.8,0.506681)
(69.4,0.500553)
y=-4.57907e-006*x*x +9.84613e-005*x + 0.516795
depth = 6 parm 26 = 10.751230 (best) with std of 0.001934
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 19.675615
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-56,0.501915)
(-40.8,0.505234)
(-25.6,0.509831)
(-10.4,0.516725)
(4.8,0.516214)
(20,0.517406)
(35.2,0.518087)
(50.4,0.517236)
(65.6,0.515108)
(80.8,0.508724)
y=-2.64713e-006*x*x +0.000134507*x + 0.516433
depth = 6 parm 27 = 25.406136 (best) with std of 0.001428
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 30.303068
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-59,0.487105)
(-42.2,0.496383)
(-25.4,0.503617)
(-8.6,0.511958)
(8.2,0.51698)
(25,0.518768)
(41.8,0.513235)
(58.6,0.505149)
(75.4,0.504894)
(92.2,0.494766)
y=-4.47664e-006*x*x +0.000199778*x + 0.513627
depth = 6 parm 28 = 22.313458 (best) with std of 0.002559
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 23.656729
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-62,0.489318)
(-43.6,0.497915)
(-25.2,0.497489)
(-6.8,0.512384)
(11.6,0.515533)
(30,0.515448)
(48.4,0.515363)
(66.8,0.512044)
(85.2,0.510682)
(103.6,0.506511)
y=-2.51208e-006*x*x +0.000211792*x + 0.510967
depth = 6 parm 29 = 42.154602 (best) with std of 0.003020
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 26.877301
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-65,0.492467)
(-45,0.496383)
(-25,0.504128)
(-5,0.512129)
(15,0.511192)
(35,0.516555)
(55,0.517406)
(75,0.514257)
(95,0.511618)
(115,0.508894)
y=-1.83526e-006*x*x +0.00019065*x + 0.51094
depth = 6 parm 30 = 51.940711 (best) with std of 0.001827
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 53.470356
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-58,0.495446)
(-36.4,0.504809)
(-14.8,0.51298)
(6.8,0.513831)
(28.4,0.513661)
(50,0.515703)
(71.6,0.513491)
(93.2,0.512129)
(114.8,0.512469)
(136.4,0.50949)
y=-1.30187e-006*x*x +0.000151669*x + 0.511467
depth = 6 parm 31 = 58.250191 (best) with std of 0.002397
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 54.125096
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-51,0.505149)
(-27.8,0.509575)
(-4.6,0.511618)
(18.6,0.513576)
(41.8,0.514086)
(65,0.515959)
(88.2,0.515959)
(111.4,0.515618)
(134.6,0.514171)
(157.8,0.513831)
y=-5.25314e-007*x*x +9.25014e-005*x + 0.511845
depth = 6 parm 32 = 88.043922 (best) with std of 0.000554
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 76.521961
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-54,0.465997)
(-29.2,0.474849)
(-4.4,0.48668)
(20.4,0.493999)
(45.2,0.506596)
(70,0.513065)
(94.8,0.514767)
(119.6,0.510171)
(144.4,0.499362)
(169.2,0.495021)
y=-2.38508e-006*x*x +0.00042604*x + 0.491526
depth = 6 parm 33 = 89.313477 (best) with std of 0.003960
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 92.056738
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-47,0.503617)
(-20.6,0.509916)
(5.8,0.511958)
(32.2,0.51298)
(58.6,0.511278)
(85,0.515278)
(111.4,0.515108)
(137.8,0.516214)
(164.2,0.513746)
(190.6,0.511278)
y=-4.45465e-007*x*x +9.32193e-005*x + 0.510302
depth = 6 parm 34 = 104.631402 (best) with std of 0.001583
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 121.215701
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-45,0.499617)
(-17,0.507788)
(11,0.509916)
(39,0.51332)
(67,0.511618)
(95,0.515959)
(123,0.51298)
(151,0.514342)
(179,0.51332)
(207,0.51281)
y=-4.67151e-007*x*x +0.000115269*x + 0.507917
depth = 6 parm 35 = 123.374648 (best) with std of 0.001800
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 109.187324
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-48,0.500128)
(-18.4,0.506171)
(11.2,0.508809)
(40.8,0.513831)
(70.4,0.515874)
(100,0.516555)
(129.6,0.514257)
(159.2,0.513576)
(188.8,0.510852)
(218.4,0.510001)
y=-6.11933e-007*x*x +0.000134457*x + 0.508415
depth = 6 parm 36 = 109.862514 (best) with std of 0.001170
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 104.931257
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-44,0.507618)
(-12.8,0.511278)
(18.4,0.513491)
(49.6,0.516214)
(80.8,0.515874)
(112,0.515618)
(143.2,0.515703)
(174.4,0.516384)
(205.6,0.515193)
(236.8,0.514001)
y=-2.68269e-007*x*x +7.06695e-005*x + 0.511972
depth = 6 parm 37 = 131.713778 (best) with std of 0.000795
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 153.056889
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-33,0.51698)
(-0.2,0.516214)
(32.6,0.515363)
(65.4,0.515789)
(98.2,0.51715)
(131,0.516214)
(163.8,0.515108)
(196.6,0.515533)
(229.4,0.515363)
(262.2,0.514171)
y=-2.45732e-008*x*x +-5.32747e-007*x + 0.51639
depth = 6 parm 38 = -10.840000 (best) with std of 0.000697
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 43.680000
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-20,0.514257)
(14.4,0.515193)
(48.8,0.515789)
(83.2,0.517576)
(117.6,0.514682)
(152,0.515108)
(186.4,0.515703)
(220.8,0.515789)
(255.2,0.515618)
(289.6,0.514767)
y=-4.74054e-008*x*x +1.32004e-005*x + 0.514993
depth = 6 parm 39 = 139.228506 (best) with std of 0.000912
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 111.214253
tking_attack[parm_no-20]
(parameter value, solution ratio)
(-5,0.516044)
(31,0.516469)
(67,0.51698)
(103,0.51715)
(139,0.515703)
(175,0.515363)
(211,0.515448)
(247,0.514171)
(283,0.514937)
(319,0.515023)
y=-1.1692e-008*x*x +-2.963e-006*x + 0.516607
depth = 6 parm 40 = -126.710638 (best) with std of 0.000673
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at -11.855319
tking_attack[parm_no-20]
(parameter value, solution ratio)
(112,0.515193)
(149.6,0.514001)
(187.2,0.515023)
(224.8,0.515703)
(262.4,0.515789)
(300,0.516384)
(337.6,0.51664)
(375.2,0.517491)
(412.8,0.51715)
(450.4,0.517576)
y=1.82436e-009*x*x +8.52251e-006*x + 0.513533
depth = 6 parm 41 = -2335.760000 (WORST) with std of 0.000477
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 450.400000
tking_attack[parm_no-20]
(parameter value, solution ratio)
(204,0.516299)
(243.2,0.515363)
(282.4,0.515789)
(321.6,0.515874)
(360.8,0.517491)
(400,0.517576)
(439.2,0.516895)
(478.4,0.51664)
(517.6,0.516044)
(556.8,0.516384)
y=-2.97928e-008*x*x +2.46666e-005*x + 0.511741
depth = 6 parm 42 = 413.968451 (best) with std of 0.000667
(-) {GOOD! We found a maximum!}
Using average of maximum value found and parabolic min at 406.984225
tking_attack[parm_no-20]
(parameter value, solution ratio)
(221,0.516895)
(261.8,0.516895)
(302.6,0.516299)
(343.4,0.516129)
(384.2,0.516299)
(425,0.517065)
(465.8,0.517236)
(506.6,0.517831)
(547.4,0.517491)
(588.2,0.518002)
y=2.38221e-008*x*x +-1.54333e-005*x + 0.519032
depth = 6 parm 43 = 323.928780 (WORST) with std of 0.000358
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 588.200000
tking_attack[parm_no-20]
(parameter value, solution ratio)
(218,0.517576)
(260.4,0.517661)
(302.8,0.517831)
(345.2,0.517321)
(387.6,0.516725)
(430,0.518002)
(472.4,0.517746)
(514.8,0.518087)
(557.2,0.517831)
(599.6,0.517576)
y=3.94536e-009*x*x +-2.50793e-006*x + 0.517943
depth = 6 parm 44 = 317.832727 (WORST) with std of 0.000424
(+) for leading coefficient of quadrati
Your evaluation function is BROKEN for this parameter.
Instead of maximizing -- we found a MINIMUM!!!
Check the sign of the term in your evaluation function
Using maximum value found at 514.800000
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Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.