The prisoner's dilemma tournament is over. There were a total of 21 entries. The winner is Margaret Sy, with a total of 39 points. 2nd and 3rd place go to rpglover64 and THE BLACK KNIGHT, with scores of 38 and 36 points respectively. There were some fairly intricate strategies in the tournament, but all three of these top scorers submitted programs that completely ignored the source code of the other player and acted randomly, with the winner having a bias towards defecting.
You can download a chart describing the outcomes here, and the source codes for the entries can be downloaded here.
I represented each submission with a single letter while running the tournament. Here is a directory of the entries, along with their scores: (some people gave me a term to refer to the player by, while others gave me a term to refer to the program. I went with whatever they gave me, and if they gave me both, I put the player first and then the program)
A: rpglover64 (38)
B: Watson Ladd (27)
c: THE BLACK KNIGHT (36)
D: skepsci (24)
E: Devin Bayer (30)
F: Billy, Mimic-- (27)
G: itaibn (34)
H: CooperateBot (24)
I: Sean Nolan (28)
J: oaz (26)
K: selbram (34)
L: Alexei (25)
M: LEmma (25)
N: BloodyShrimp (34)
O: caa (32)
P: nshepperd (25)
Q: Margaret Sy (39)
R: So8res, NateBot (33)
S: Quinn (33)
T: HonoreDB (23)
U: SlappedTogetherAtTheLastMinuteBot (20)
Can you elaborate on this?
You are right that I used the inflammatory t-word because CooperateBot submitters are probably not trying to win. I certainly expected to see DefectBots (or CliqueBots from optimists), and agree that the competition should have been seeded with both CooperateBots and DefectBots.
But I don't understand this at all:
To me, this looks like t-wording the people who play 0.
Are we thinking of the same game, where the payout is constant?
Yes, that game. My point is that complaining "that's not fair, X player wasn't playing to win" is a failure to think like reality. You know that you're playing against humans, and that humans do lots of things, including playing games in a way that isn't playing to win. You should be taking that into account when modeling the likely distribution of opponents you're going to face. This is especially true if there isn't a strong incentive to play to win.