MD ladder is probably significantly tougher to solve with a single agent than the official ladder (with just one template, it's a lot easier to encode things- otherwise, I think you'll need your input representation to encode the map/settings as well or alternatively maybe try some crazy image recognition thing where you hope it's able to figure out the map by itself).
I think a competitive recurrent network-based agent is probably viable with current technology, although it probably won't be able to consistently beat ladder #1's. I don't know enough about other approaches (incl. Monte Carlo tree search, which is what AlphaGo used) to comment on their applicability to Warlight.
That said, while state-of-the-art AI is currently able to do some impressive things, it's worth noting that it's still more restricted than you'd expect. If a human figured out how to be really good at Go, for example, you'd expect them to be able to do a few other things that require (for humans) less intelligence- but AI doesn't translate that way. That's because, at the end of the day, all we're really doing is cleverly finding mathematical operations that seem to work well for a given task. AI doesn't think, or even really learn (at least not in a way similar to humans- neural networks are modeled after our brains, ofc, but current learning algorithms aren't very similar to how you and I learn, and some things that are basic to humans are still unsolved problems in the realm of AI research).
Even some networks that seem to work very well- image recognition, for example- can be fragile. You can make visually unnoticeable changes to an image and completely trick a neural network to classifying it as something else. (see: https://blog.keras.io/the-limitations-of-deep-learning.html
Honestly, it's easier than you might realize to try building a deep network that does a good job on the WL MD ladder (you probably won't be able to do it rigorously, but I bet there's a few architectures out there that would adapt well to WL), especially if you have the time to tweak some behaviors manually. But actual AI dominance of humans is probably very far away; I'm kind of hoping we figure out better fundamental techniques in the meanwhile.
Edited 9/9/2017 04:08:23