The script glennie.py allows comparison of White’s moves from the TUROCHAMP—Glennie game with PyTuroChamp’s moves. Changing the parameters in pyturochamp.py will yield different results.
The best match is observed with PSTAB = 0, MAXPLIES = 1, QPLIES = 7 (or greater):
$ pypy3 glennie.py
pstab = 0, maxplies = 1, qplies = 7
# orig PTC
1 e2e4 e2e3
4 g1f3 d1d3
6 d4d5 a2a3
10 f1b5 d2e3
15 h1g1 e1g1
17 a6b5 a6c4
19 b5c6 e2c4
22 c1d2 e2e3
23 g5g4 b2b3
25 d5b3 d1g1
26 b3c4 d2e2
27 g4g3 g4g5
===> 12 moves differThis is similar to the ChessBase Turing Engine, which produces 11 mismatches (in moves 1, 5, 15, 17, 18, 19, 20, 22, 23, 27, and 29), although the CB and PTC moves are seldom the same.
These best-fit parameters also agree with Turing’s text who specified a brute-force depth of two plies (equal to MAXPLIES = 1 in the case of PTC) and a high but unknown selective search depth (QPLIES).
Turing’s idea to evaluate material by dividing White’s value by Black’s value (instead of subtracting Black from White) can also be tested. The only difference is in move 17, where “W/B” plays h4h5 and “W-B” plays a6c4.
According to Stockfish analysis, the “W-B” move is also the only winning move for White, while the “W/B” move leads to a drawn position. So at least in this game, “W/B” is inferior to “W-B”. (Also note that in the Glennie game, TUROCHAMP plays 17. a6b5, which is a blunder and possibly caused by a wrong computation of TUROCHAMP’s moves by Turing and Glennie.)
$ pypy3 kasparov.py
pstab = 0, maxplies = 1, qplies = 7
3 g1h3 h2h4
5 f1d3 a2a4
8 e4g3 e1g1
9 e1g1 b2b3
15 f1e1 c4b5
===> 5 moves differThe ChessBase TUROCHAMP implementation does not play TUROCHAMP’s signature moves a4 or h4 and prefers 3. Nh3 instead. As Andre Adrian notes, this probably means ChessBase TUROCHAMP has a bug, since the Knight would have more mobility on f3.
A similiar comparison can be done to the SOMA game recorded in New Scientist (November 9, 1961; page 369) using somatest.py.
Taking into account the random move selection feature of SOMA, the best-matched game from soma.py includes eight moves that differ from those given in the New Scientist article. (Soma.py’s own moves also vary due to randomness of course.)
However, the description of the SOMA algorithm in New Scientist leaves out some details, so a few differences are to be expected. Also, SOMA’s moves in the 1961 article were computed by the article’s author, not a computer, so errors in computation are a possibility.
# orig soma.py
2 d2d4 d1g4
3 b1c3 g1f3
7 c1d2 d1h5
10 f1e2 f2f3
13 f3e4 e2a6
18 e2f3 e2d3
24 d5b5 d5d8
27 e4f5 a5c3