update docs for v5.8.0

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docs/benchmark/5_7_0/en/index.md

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+# [Othello research support AI app Egaroucid](https://www.egaroucid-app.nyanyan.dev/) Benchmarks
+
+<a href="https://twitter.com/share?ref_src=twsrc%5Etfw" class="twitter-share-button" data-text="Othello research support AI app Egaroucid" data-url="https://www.egaroucid-app.nyanyan.dev/" data-hashtags="egaroucid" data-related="takuto_yamana,Nyanyan_Cube" data-show-count="false">Tweet</a><script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> <a href=./../ja/>日本語</a>
+
+Version 5.5.0 and 5.6.0
+
+## FFO endgame test
+
+FFO endgame test is a famous test to evaluate endgame solvers.
+
+I did complete searches for this test and got the time to solve it and number of nodes searched.
+
+* depth: search depth
+* whole time: search time including some other calculation in milliseconds
+* policy: the best move
+* nodes: number of nodes visited
+* nps: node per second
+
+### Core i9-11900K, 16 threads
+
+<div style="font-size:60%"><pre>#40 depth 20 value 38 policy a2 nodes 32617519 time 187 nps 174425235
+#41 depth 22 value 0 policy h4 nodes 26560625 time 242 nps 109754648
+#42 depth 22 value 6 policy g2 nodes 51191219 time 360 nps 142197830
+#43 depth 23 value -12 policy c7 nodes 168771687 time 929 nps 181670276
+#44 depth 23 value -14 policy d2 nodes 43705622 time 626 nps 69817287
+#45 depth 24 value 6 policy b2 nodes 973544606 time 4256 nps 228746382
+#46 depth 24 value -8 policy b3 nodes 169047118 time 2315 nps 73022513
+#47 depth 25 value 4 policy g2 nodes 115350803 time 816 nps 141361278
+#48 depth 25 value 28 policy f6 nodes 822747204 time 4137 nps 198875321
+#49 depth 26 value 16 policy e1 nodes 1021389690 time 6387 nps 159916970
+#50 depth 26 value 10 policy d8 nodes 3470416861 time 15945 nps 217649223
+#51 depth 27 value 6 policy a3 nodes 2093326335 time 19308 nps 108417564
+#52 depth 27 value 0 policy a3 nodes 666596389 time 7950 nps 83848602
+#53 depth 28 value -2 policy d8 nodes 12227417145 time 67989 nps 179844050
+#54 depth 28 value -2 policy c7 nodes 13290990536 time 71954 nps 184715103
+#55 depth 29 value 0 policy b7 nodes 41506305139 time 276500 nps 150113219
+#56 depth 29 value 2 policy h5 nodes 3409497345 time 28172 nps 121024327
+#57 depth 30 value -10 policy a6 nodes 13317806725 time 88863 nps 149868974
+#58 depth 30 value 4 policy g1 nodes 4861384409 time 31941 nps 152198879
+#59 depth 34 value 64 policy g8 nodes 2975 time 1624 nps 1831
+630.501 sec
+631.2902810573578 sec total
+98268669952 nodes
+155858071.52090162 nps</pre></div>
+
+
+
+
+
+## Play against Edax4.4
+
+Edax is one of the best othello AI in the world.
+
+If I set the game from the very beginning, same line appears a lot. To avoid this, I set the game from many different lines. These lines, boards in [XOT](https://berg.earthlingz.de/xot/index.php), are not in learning data of evaluation function.
+
+No book used.
+
+* start depth: the depth of the line
+* WDL: win-draw-lose
+* Egaroucid win rate: Egaroucid's win rate excluding draws
+
+if the win rate is over 0.5, Egaroucid win more than Edax do.
+
+### Level 1
+
+Lookahead depth is 1, complete search depth is 2
+
+<div style="font-size:60%"><pre>start depth: 8 Egaroucid plays black WDL: 61-2-67 Egaroucid plays white WDL: 76-3-51 Egaroucid win rate: 0.5372549019607843
+</pre></div>
+
+### Level 5
+
+Lookahead depth is 5, complete search depth is 10
+
+<div style="font-size:60%"><pre>level 5
+start depth: 8 Egaroucid plays black WDL: 68-6-56 Egaroucid plays white WDL: 67-11-52 Egaroucid win rate: 0.5555555555555556</pre></div>
+
+
+### Level 11
+
+Lookahead depth is 11. Selectivity is 73% (to align the conditions, Egaroucid uses the same selectivity as Edax). The depth of complete search is also the same.
+
+<div style="font-size:60%"><pre>level 11
+start depth: 8 Egaroucid plays black WDL: 69-18-43 Egaroucid plays white WDL: 61-15-54 Egaroucid win rate: 0.5726872246696035</pre></div>
+
+
+
+## Accuracy of evaluation function
+
+The mse (mean squared error) and mae (mean absolute error) of my evaluation function.
+
+30 evaluation functions are used in Egaroucid, for each 2 moves.
+
+Evaluation function of phase X is used 2X + 1 moves to 2X + 2 moves.
+
+<div style="font-size:60%"><pre>phase 0 mse 184.415 mae 9.79577
+phase 1 mse 181.731 mae 9.74168
+phase 2 mse 176.078 mae 9.61612
+phase 3 mse 166.574 mae 9.39029
+phase 4 mse 153.356 mae 9.05595
+phase 5 mse 273.548 mae 12.0107
+phase 6 mse 94.0067 mae 7.18964
+phase 7 mse 87.0103 mae 6.94262
+phase 8 mse 80.5171 mae 6.70287
+phase 9 mse 73.5077 mae 6.42004
+phase 10 mse 67.8453 mae 6.13735
+phase 11 mse 62.4096 mae 5.91408
+phase 12 mse 57.1586 mae 5.69015
+phase 13 mse 51.493 mae 5.42289
+phase 14 mse 45.5248 mae 5.11642
+phase 15 mse 39.6584 mae 4.78097
+phase 16 mse 36.1119 mae 4.56925
+phase 17 mse 32.6206 mae 4.34778
+phase 18 mse 29.1944 mae 4.12316
+phase 19 mse 28.7966 mae 4.10928
+phase 20 mse 29.1392 mae 4.15409
+phase 21 mse 29.9168 mae 4.22495
+phase 22 mse 31.1575 mae 4.32002
+phase 23 mse 33.4589 mae 4.478
+phase 24 mse 33.8493 mae 4.50079
+phase 25 mse 32.3792 mae 4.39883
+phase 26 mse 29.3648 mae 4.17235
+phase 27 mse 24.5691 mae 3.80085
+phase 28 mse 16.3138 mae 3.05533
+phase 29 mse 4.51746 mae 1.3841</pre></div>
+
+
+
+## Other versions
+
+* [5.4.1](./../5_4_1)
+* [5.5.0 and 5.6.0](./../5_5_0)
+

docs/benchmark/5_7_0/index.html

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