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I struggled for years to develop an AI that played the computer strategy for Empire.

http://www.classicempire.com/

I'd just run games, look at results, and endlessly tweak the strategy. Recently I learned how neural networks worked, and realize I could finally make a computer strategy that was competent. It could be trained by playing zillions of games against itself.

My only defense is that training a neural network was impractical on the machines Empire was developed on.

It's hard to resist going back to Empire and doing this.



How you ended up implement it in the code? Is it just a heuristic implemented as a series of if/else/case statements? Minimax? Thank you

EDIT: sorry, I found out that source code is available, I will try to find it

EDIT2: Looks like it's up for sale, not open


https://github.com/DigitalMars/Empire-for-PDP-10

It's the same algorithm. Mainly a bunch of ad-hoc heuristics.




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