I see one major drawback in your proposal:
You re NOT creating an AI, you are proposing a rule based decision making machine. It makes no difference whether you implement it as a flow chart diagram or in python, it will not be intelligent at all. In your codebase there is a file called machine_learning, an approach equally unfit for an "AI" in this kind of games, because finding similar events and training accordingly is really complex here, look at this (slightly mathematical) approach:
In go your there are 19*19 = 361 fields where a value can be. This yields a search space of (at max) a dimension of 361 to find situations and appropriate reactions. This problem was not solvable on a PC.
Now consider dual universe. There are way more than 361 values that can (and should) influence your decision making as well as no data on how to react on those. And there is another problem: keeping all values up to date and produce similar results on similar actions. The first problem will most likely only be addressable if Novaquark grants access to Dual Universe for such a system, but the second is way worse. Given the following scenario:
A huge ship attacks one of your stations (one that can take out all your ships at ease), what do you do? Next time it is only a small fighter. So learning will be extremely expensive for your org as well as hardly reproducible because the correct reaction can hardly drawn from incomplete data.
These are all concerns regarding governance "AI", I wish you best luck, seems to be an interesting approach either way.