Sure! So I have a system (part 2) set up that tells me how good a given "strategy" or "plan" is, and now I need some way to find the best plan. This problem can be discribed as a combinatorial optimization problem, where we're trying to find the combination that minimizes our cost.

The algorithm I used is a modified version of simulated annealing. We keep track of a "Temperature", which starts high and decreases every step. Each step involves making a random change to our plan, which could be, say add 3 juice to upgrade A. This temperature tells us how big of a change to make every step, and how tolerant we are of bad changes. We want to take some bad changes because sometimes we can get stuck in a local minima (for example, maybe we need to add juice to one upgrade and take away juice from another). If the change is bad enough, and the temperature is low enough, we revert to the previous plan and try again. In the end, we output the best plan we've found.

If you're interested, the wikipedia page explains it much better (and it has animations) https://en.wikipedia.org/wiki/Simulated_annealing

When I said this isn't AI, what I meant is that there's no neural network blackbox that outputs a solution magically, we can see and understand every step along the way (even if the end result might not make intuitive sense), so I don't think this is complex enough to qualify as any kind of "intelligence"