September 19, 2020

Bots Play Backgammon Too

Responding to my entry yesterday about pokerbots, Jordan Lampe emails a report from the world of backgammon. Backgammon bots play at least as well as the best human players, and backgammon is often played for money, so the temptation to use bots in online play is definitely there.

Most people seem to be wary of this practice, and the following
countermeasures have been developed (not necessarily exclusive or all
used by the same person)

1) Don’t play for money; only play for fun
2) Play money only against people you know [well]
3) Against somebody who takes a long time after every move, you are
suspicious that they are plugging their moves into computers
4) At the end of the game, you can analyze your game with one of the
computer programs. It turns out that all the computers rate each
other’s play very highly, with an error rate of 0-1.5 “millipoints” per
move. If you get a rate of exactly 0 you can be dead certain they are
using the same computer program. Computers rate the best humans in the
world in the 3-4 range. In any case, if your opponent is using a
computer program to decide all his moves it is fairly easy to tell after
only a few games, and then avoid playing with that player any more.
5) Some players take the attitude, “if I lose, at least I’ll have
learned something” and therefore ignore if they are playing bots
6) Using a bot to help you win is, well, boring, and so it doesn’t
happen that much anyway

Having played a lot of poker and backgammon in my day, I suspect that distinguishing human play from computer play would be harder in poker than it is in backgammon. For one thing, in backgammon you always know what information your opponent had in choosing a certain move (both players have the same information at all times); but in poker you may never know what your opponent knew or believed at a particular point in time. Also, a good poker player is always trying to frustrate opponents’ attempts to build mental models of his decision processes; this type of misdirection, which a good bot will emulate by using randomized algorithms, will make it harder to distinguish similar styles of play.

Jordan identifies another factor that several poker players mentioned as well: the fact that most gambling income is made by separating weak players from their money. As long as there are enough “fish”, all of the sharks, whether human or not, will feast. When the stakes get high, the fish will be driven out; but at low stakes, good human players may still make money.