Similar things weren't really said about Go or Chess. Both are perfect information games so, by definition, they can't involve deceit There's no need to try to detect subtle patterns in your opponents behavior because you have the entire game in front of you. That's not to say it's impossible but they do very much have their work cut out for them. It's an entirely different type of game that is much more difficult than Go and Chess.
> Similar things weren't really said about Go or Chess. Both are perfect information games so, by definition, they can't involve deceit
I took deceit to mean tricking your opponent into thinking you were doing one thing when you were actually going to do another. You can't do that in Go or Chess?
What I generally meant was maybe there's some really boring numerical number crunching or some simple mechanical algorithm that solves games like StarCraft but when humans talk about it, they talk about mind games, deceit, intimidation etc. when maybe these things are irrelevant.
>I took deceit to mean tricking your opponent into thinking you were doing one thing when you were actually going to do another. You can't do that in Go or Chess?
Well you can technically but it's horrible. No above amateur player tries to play 'trick moves'. Skilled players try to find the objectively best moves in the given position because tricks are just way to easily spotted.
The "betcha didn't see that coming!" thing is only something they do in dramatised films. Stracraft and other RTS games on the other hand abuse lack of information quite heavily. 'Cheese strategies' or unorthodox openings are very frequently used at the highest level.
Yes, people play silly moves once in two decades, but again, in 99.9% of games nobody swindles or plays a6. In starcraft a good third of pro games or something involves cheesy openings.
Deceit boils down to assuming your opponent will misjudge the situation and make a mistake. In Chess or Go, computer players choose the best move assuming that the opponent won't make any mistakes (will never be fooled). There's no attempt to model a weaker opponent.
This is why computer players in Go tend to fall apart when they start losing. They don't see a path to victory against a perfect opponent, so all moves look the same.
A Go AI that can win from behind (given a handicap) might be an interesting challenge.
> In Chess or Go, computer players choose the best move assuming that the opponent won't make any mistakes (will never be fooled). There's no attempt to model a weaker opponent.
What I meant was there's no reason an AI couldn't try to fool a human in a perfect information context. For example, you could bait a (probably not world class though) opponent into capturing a piece which puts them in a bad position, where certain baits are more likely to work on humans than others. There's plenty of situations in real life where two people have the same information but one comes out on top because the other overlooked a detail.
> This is why computer players in Go tend to fall apart when they start losing. They don't see a path to victory against a perfect opponent, so all moves look the same.
Is this not a limitation of the AI though instead of something inherent to AI?
> A Go AI that can win from behind (given a handicap) might be an interesting challenge.
It's more of a testing limitation. These programs are only occasionally tested against humans. You need expert players to test, they're not available all the time, and it takes a long time to play a single game (unlike poker). You can use databases of online games but it won't tell you how the player would have responded to a different move 37.
If you're writing a program to beat anyone, there isn't much point in optimizing the algorithm for a specific opponent's weaknesses when there are improvements to make that would work against anyone and the improvement in strength can be evaluated using computer testing alone.
Work on exploiting specific opponents' weaknesses is typically done using much simpler games (check out what's been done for rock paper scissors).