interview with Aaron Hall

[abkaiser]

Ed Kolis said:
Don't worry, I have no idea what Bayesian networks are either... perhaps they're something like neural networks???

Genetic algorithms = code that evolves like a living species.

My limited understanding: A Bayesian network uses mass amounts of data to predict a situation's probable outcomes, and therefore determine how to behave. Similar to looking for a "law of averages" on a really big scale.

That's all I can tell you - Not being a programmer, I don't know how this is applied to game theory.

Andy

[Aiken]

abkaiser said:That's all I can tell you - Not being a programmer, I don't know how this is applied to game theory.

Allows AI to effectively use incomplete information about its enviroment to make decisions in uncertain situations with many possible outcomes. Good for long term planning.
Drawbacks are serious requirements in computational power and need for primary accumulation of info.

Not a coder too - used it for urban development model.

More: http://www.niedermayer.ca/papers/bayesian/bayes.html

[Will]

Technically, bayesian nets would not be used for an AI. All they do is generate probabilities, based on known data. The AI would only come in when you make decisions based on these predicted probabilities.

I guess you could kludge together an AI that "learns" what actions to take using Bayes nets, by observing the data availible to a human player, and noting the probablilities of certain actions. This could create the interesting possibility of an AI that plays just like a particular human player. Only the AI would still not be able to generate their own strategies, only go off observed strategies.