Can a Bayesian Spam Filter Play Chess? 204
martin-boundary writes "The typical Bayesian spam filters learn to distinguish ham from spam just by reading thousands of emails, but is this all they can do?
This essay shows step by step how to teach a Bayesian filter to play chess against a human, on Linux, with
XBoard."
Re:Results? (Score:3, Informative)
Gaaah! Google's cache doesn't have that onepage!
For all the others, try here [google.com]
J.
Re:Results? (Score:5, Informative)
Not really. But it does work, and it would be possible from someone to take this and expand on it quite neatly.
For example, it currently uses entire games to compare. So if it comes across an unusual opening, even one close to a standard one, it's not able to decide effectively. Perhaps something using game fragments would be possible, then it might reproduce structured plays even when the previous game play has been unusual.
Really though, it is a successful tiny step in a direction that no-one else has thought of going. That's worth congratulating in and of itself.
So... anyone got any other suggestions for improvements?
Justin.
anything (Score:1, Informative)
Re:problem building dbacl (Score:3, Informative)
Re:The point? (Score:3, Informative)
Spam filters are a good tool used to filter spam.
I agree with you that spam filters need to improve, including others tools _in_addition_to_ bayesian filters.
Nevertheless, seeing that bayesian filters are just a tool used in spam filters, your claims are nonsensical. Bayesian filters existed before spam filters, and they have lots of applications. In fact, this is not the first time a bayesian filter is applied to chess.
Bayesian filters are good at anything that requires automatic learning (kind of a self-evolving AI), that only needs a measure of success and failure to mold its behaviour.
Chess is even better suited than spam, because you don't need a user to tell the filter whether it succeeded in playing a match, like it happens with spam filtering.
AI Koan (Score:3, Informative)
"What are you doing?", asked Minsky.
"I am training a randomly wired neural net to play Tic-Tac-Toe", Sussman replied.
"Why is the net wired randomly?", asked Minsky.
"I do not want it to have any preconceptions of how to play", Sussman said.
Minsky then shut his eyes.
"Why do you close your eyes?", Sussman asked his teacher.
"So that the room will be empty."
At that moment, Sussman was enlightened.