December 18, 2018

Archives for September 2004

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.

Online Poker and Unenforceable Rules

Computerized “bots” may be common in online poker games according to a Mike Brunker story at MSNBC.com. I have my doubts about the prevalence today of skillful, fully automated pokerbots, but there is an interesting story here nonetheless.

Most online casinos ban bots, but there is really no way to enforce such a rule. Already, many online players use electronic assistants that help them calculate odds, something that world-class players are adept at doing in their heads. Pokerbot technology will only advance, so that even if bots don’t outplay people now, they will eventually. (The claim, sometimes heard, that computers cannot understand bluffing in poker, is incorrect. Game theory can predict and explain bluffing behavior. A good pokerbot will bluff sometimes.)

Once bots are better than people, it’s hard to see why a rational person, with real money at stake, would fail to use a bot. Sure, watching your bot play is less fun than playing yourself; but losing to a bunch of bots isn’t much fun either. Old-fashioned human vs. human play will still be seen in very-low-stakes online games, where it’s not worth the trouble of deploying a bot, and in in-person games where the non-botness of players can be checked.

The online casinos are kidding themselves if they think they can enforce a no-bots rule. How can they tell what a player is doing in the privacy of his own home? Even if they can tell that a human’s hands are on the keyboard, how can they tell whether that human is getting advice from a bot?

The article discusses yet another unenforceable rule of online poker: the ban on collusion between players. If two or more players simply show each other their cards, they gain an advantage over the others at the table. There’s no way for an online casino to prevent players from conducting back-channel communications, so a ban on collusion is impossible to enforce.

By reiterating their anti-bot and anti-collusion rules, and by claiming to have mysterious enforcement mechanisms, online casinos may be able to stem the tide of cheating for a while. But eventually, bots and collusion will become the norm, and lone human players will be driven out of all but the lowest stakes games.

But there is another strategy. An online casino could encourage bots, and even set up bots-only games. The game would then become not a human vs. human card game but a human vs. human battle between bot designers for geekly mastery. I’ll bet there are plenty of programmers out there who would like to give it a try.

Voluntary Filtering Works for Us

It’s day two of porn week here at Freedom to Tinker, and time to talk about the tools parents have to limit what their kids see. As a parent, I have not only an opinion, but also an actual household policy (set jointly with my wife, of course) on this topic.

Like most parents, we want to limit what our kid sees. The reason is not so much that there are things we want our kid never to see, but more that we don’t think our kid is ready, yet, to see and hear absolutely everything in the world. Even the Cookie Monster is scary to kids at a certain age. Good parents know what their kids can handle alone, and what their kids can handle with a trusted adult present. We want to expose our kid to certain things gradually. Some things should be seen for the first time with a parent present to talk about what is being depicted.

But how can we do this, in the real world? It’s not enough simply to say that we should supervise our kid. To watch a kid nonstop, 24/7, is not only impractical but creepy. We don’t want to turn our home into a surveillance state.

Instead, we rely on architecture. For example, we put the only kid-accessible computer and TV in the busiest room of the house so that we’re less likely to lose track of what’s happening. But even that isn’t foolproof – it doesn’t work in the early morning hours when kids tend to be up while parents sleep.

This is where filtering technology can help. We find the TV rating and filtering system quite useful, despite its obvious flaws. This system is often called the V-chip, but we don’t actually rely on the V-chip itself. Instead, we rely on our Tivo to allow restrict access to shows with certain ratings, unless a secret password has been entered. We know that the technology overblocks and underblocks. But overall, we prefer a policy of “watch any kid-rated show you want, but ask a parent if you want to watch anything else” to the alternatives of “watch anything you want” or “always ask a parent first”. (A welcome side-effect: by changing the rating threshold we can easily implement a “no TV today” policy.)

It’s worth noting that we don’t use the federally mandated V-chip, which is built into our TV. We simply use the ratings associated with shows, and the parental controls that Tivo included voluntarily in its product. For us, the federal V-chip regulation provided, at most, the benefit of speeding standardization of the rating system. We’re happy with a semi-accurate, voluntary system that saves us time but doesn’t try to override our own judgment.