If you had lots of end states, and lots of non-end states, and we want to assume the game ends when someone’s won, and
that a player only moves into an end state if he’s won (neither of these last two are necessarily true even in nice pretty games), then you could treat it like a classification problem. In that case, you could throw your favourite classifier learning algorithm at it. I can’t think of any publications on someone machine learning a winning condition, but that doesn’t mean it’s not out there.
Dr. David Silver used temporal difference learning to learn some important spatial patterns for Go play, using self-play. Self play is basically like watching yourself play lots of games with another copy of yourself, so I can imagine similar ideas being used to watching someone else play. If you’re interested in that, I suggest http://www.aaai.org/Papers/IJCAI/2007/IJCAI07-170.pdf
On a sadly less published (and therefore mostly unreliable) but slightly more related note, we did have a project once in which we were trying to teach bots to play a Mortal Kombat style game only by observing logs of human play. We didn’t tell one of the bots the goal, we just told it when someone had won, and who had won. It seemed to get along ok.
If you had lots of end states, and lots of non-end states, and we want to assume the game ends when someone’s won, and that a player only moves into an end state if he’s won (neither of these last two are necessarily true even in nice pretty games), then you could treat it like a classification problem. In that case, you could throw your favourite classifier learning algorithm at it. I can’t think of any publications on someone machine learning a winning condition, but that doesn’t mean it’s not out there.
Dr. David Silver used temporal difference learning to learn some important spatial patterns for Go play, using self-play. Self play is basically like watching yourself play lots of games with another copy of yourself, so I can imagine similar ideas being used to watching someone else play. If you’re interested in that, I suggest http://www.aaai.org/Papers/IJCAI/2007/IJCAI07-170.pdf
On a sadly less published (and therefore mostly unreliable) but slightly more related note, we did have a project once in which we were trying to teach bots to play a Mortal Kombat style game only by observing logs of human play. We didn’t tell one of the bots the goal, we just told it when someone had won, and who had won. It seemed to get along ok.