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I'm interested in how strategic AI engines work, e.g. how to evaluate where to place troops in a turnbased strategy game etc.

I do get how goal based AI works, and I guess that is a good approach to decide what to build or research in a game like Civilization.

But tactical/strategical positioning of troops/units. What algorithms/strategies are used to evaluate those things? any reference papers/articles?

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You might find reading the book "Artificial Intelligence for Games" very helpful. It gives you insight in the AI implementation of various kinds of games. (e.g. troop placement/movement, path finding, decision trees, ..)


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Possibly not the best solution, but decision trees, specifically a minimax tree may be a good approach to take. See

You would need to create a heuristic function which can determine how good/bad a world state is. But this can become a bit more complicated if you are working with a large number of possible world states.

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Artificial Intelligence is, unfortunately, an entire subsection of Computer Science. It's truly huge - something you can take a couple of semesters of in college just to get you warmed up.

There are a lot of common options - Decision Trees, Rules Engines, Neural Networks - the latter of which most people tend to find extremely interesting when they first hear about them (and invariably prove to be a horrible idea in the kind of scenario you're describing - look out for that). I recommend you look up some topics or books on basic AI development in general - it may not seem directly relevant to games specifically at first, but you'll appreciate understanding the fundamentals.

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Have a look at Monte Carlo Tree Search (like min max but prunes the kind of large trees you see in games these days with large branching factors).

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