The purpose of this study is to determine the effects of additional computing power for scalable 13x13 Computer Go programs. The programs that are being tested use a popular new technique based on Monte Carlo simulations (randomly played games in this case) combined with best first tree searching called UCT.
This study tests programs at many different level in a competition for ELO rating points. Elo ratings are a direct measure of playing strength. Each version of a particular program spends twice as much effort playing it's move as the previous version, as measured by the number of random games played to choose a move.
Matches are scheduled between players using a random scheduling algorithm where players of similar strength are much more likely to play each other, but any pairing is still possible. This works far better for assessment purposes than, for instance, a round robin where matches between players of considerably different skill are common.
The amount of computing effort required to test these programs at higher levels is substantial and several people have contributed computing resources to this effort. On a single computer this study would require many months of computing effort in order to get enough data to be statistically meaningful.
Currently, two programs are participating in this study, Mogo, and Leela. Mogo is one of the strongest, if not strongest, 13x13 go playing program in the world at this time (early 2008.) Leela is also one of the top playing programs on the CGOS server at small board sizes.
One additional program plays as a reference point, a popular open source program called "Gnugo" which plays at a fixed level of 1800 ELO.
In the following table, there are various versions of mogo, labeled 01, 02, 03, .... Mogo_01 does only 128 monte carlo simulations in the evaluation porition of the tree search. Mogo_02 doubles this and each subsequent version doubles the previous in number of simulations.
Likewise, Leela is labelled similarly. Both Leela and Mogo do the same number of simulations at the coresponding levels, i.e. 128 monte carlo simulation at level 01.
We can compute the number of simulations for any level as:
Mogo and Leela simulations at level N = 128 * 2^(N-1)
| Rank | Name | Elo | + | − | Games | score | opponent |
|---|---|---|---|---|---|---|---|
| 1 | Mogo_13_15 | 2880 | 21 | 20 | 2340 | 84% | 2457 |
| 2 | Mogo_13_14 | 2808 | 19 | 18 | 2614 | 79% | 2396 |
| 3 | Mogo_13_13 | 2717 | 16 | 16 | 3039 | 70% | 2423 |
| 4 | Leela2_13 | 2638 | 21 | 21 | 2367 | 80% | 2191 |
| 5 | Mogo_13_12 | 2610 | 16 | 16 | 3051 | 60% | 2428 |
| 6 | Leela2_12 | 2548 | 20 | 20 | 2451 | 75% | 2159 |
| 7 | Mogo_13_11 | 2493 | 15 | 15 | 3656 | 61% | 2331 |
| 8 | Leela2_11 | 2437 | 20 | 20 | 2458 | 70% | 2106 |
| 9 | Mogo_13_10 | 2380 | 14 | 15 | 3733 | 50% | 2330 |
| 10 | Leela2_10 | 2332 | 18 | 18 | 2625 | 63% | 2113 |
| 11 | Mogo_13_09 | 2270 | 13 | 13 | 4789 | 54% | 2218 |
| 12 | Leela2_09 | 2213 | 19 | 19 | 2613 | 61% | 2008 |
| 13 | Mogo_13_08 | 2147 | 13 | 13 | 4788 | 44% | 2195 |
| 14 | Leela2_08 | 2085 | 19 | 19 | 2656 | 58% | 1925 |
| 15 | Mogo_13_07 | 2022 | 13 | 13 | 4693 | 43% | 2100 |
| 16 | Leela2_07 | 1932 | 18 | 19 | 2658 | 56% | 1818 |
| 17 | Mogo_13_06 | 1903 | 13 | 13 | 4586 | 43% | 1967 |
| 18 | Leela2_06 | 1806 | 18 | 18 | 2688 | 56% | 1687 |
| 19 | Gnugo-3.7.11 | 1800 | 12 | 11 | 6506 | 57% | 1751 |
| 20 | Mogo_13_05 | 1765 | 13 | 13 | 4542 | 45% | 1802 |
| 21 | LightLeela_13 | 1745 | 28 | 28 | 969 | 48% | 1802 |
| 22 | LightLeela_12 | 1696 | 28 | 28 | 964 | 47% | 1764 |
| 23 | LightLeela_11 | 1631 | 29 | 29 | 974 | 46% | 1705 |
| 24 | Leela2_05 | 1621 | 19 | 19 | 2772 | 51% | 1583 |
| 25 | Mogo_13_04 | 1599 | 12 | 12 | 6046 | 45% | 1631 |
| 26 | LightLeela_10 | 1551 | 30 | 30 | 967 | 46% | 1613 |
| 27 | LightLeela_09 | 1462 | 30 | 30 | 969 | 44% | 1559 |
| 28 | Leela2_04 | 1412 | 20 | 20 | 2785 | 47% | 1458 |
| 29 | LightLeela_08 | 1357 | 31 | 31 | 979 | 44% | 1473 |
| 30 | Mogo_13_03 | 1338 | 15 | 15 | 5538 | 49% | 1359 |
| 31 | LightLeela_07 | 1223 | 31 | 31 | 1021 | 41% | 1384 |
| 32 | Leela2_03 | 1169 | 20 | 20 | 2811 | 41% | 1334 |
| 33 | LightLeela_06 | 1124 | 31 | 31 | 1034 | 40% | 1322 |
| 34 | Mogo_13_02 | 1041 | 13 | 13 | 5500 | 54% | 1082 |
| 35 | LightLeela_05 | 946 | 31 | 31 | 1020 | 39% | 1190 |
| 36 | Leela2_02 | 913 | 19 | 20 | 2783 | 31% | 1236 |
| 37 | LightLeela_04 | 824 | 30 | 31 | 1027 | 33% | 1152 |
| 38 | Mogo_13_01 | 745 | 15 | 16 | 4879 | 16% | 1185 |
| 39 | Leela2_01 | 693 | 21 | 22 | 2729 | 16% | 1233 |
| 40 | LightLeela_03 | 643 | 32 | 32 | 1023 | 26% | 1102 |
| 41 | LightLeela_02 | 468 | 34 | 35 | 1027 | 16% | 1062 |
| 42 | LightLeela_01 | 370 | 38 | 41 | 1032 | 9% | 1094 |
Command line program invocation (weakest level)
| Mogo | mogo --13 --nbTotalSimulations 128 --playsAgainstHuman 0 |
| Leela | leela 7 note: level N = 2 ^ N |
| Leela Lite | leelaLight 7 note: level N = 2 ^ N |
| Gnugo-3.7.11 | gnugo --mode gtp --capture-all-dead --chinese-rules --min-level 10 --max-level 10 --positional-superko |
| X axis: | Each CPU Doubling |
| Y axis: | ELO Rating |