interview with Aaron Hall

[Ed Kolis]

Who says recursion wouldn't be possible? As long as he lets us define functions, couldn't we do something like this:

Code:

---

function plan(n) {

  if n > 0 {

    plan(n-1)

    // plan ahead for turn now + n

  }

  else {

    // do stuff for this turn

  }

}

---

We'd just have to make sure not to code any infinite loops

[abkaiser]

Ed Kolis said:
Who says recursion wouldn't be possible? As long as he lets us define functions, couldn't we do something like this:

Code:

---

function plan(n) {

  if n > 0 {

    plan(n-1)

    // plan ahead for turn now + n

  }

  else {

    // do stuff for this turn

  }

}

---

We'd just have to make sure not to code any infinite loops

It depends:

1) We wouldn't be using a commercial development package for this. Like you said, the AI parser/compiler would be done using tools Aaron and the dev team provide, so that functionality is up to them.

2) Would they even want to implement recursion for us, with all the implications we've both mentioned?

3) And how much power do they want to give to recoding the AI versus more limited customization? Space Empires isn't open source. I could even see someone coming up with a really whiz-bang AI mod and selling it for profit.

Andy

[narf poit chez BOOM]

aiken said:
Superb code Ed

Though, if-elif-else's are nice for simple finite state machines, they're not sufficient to write something decent. I seriously hope it will be possible to code a bayesian networks (or even implement a genetic algos!!) with this scriptining language.

/me crosses fingers

Huh?

[Ed Kolis]

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.

[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.