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You aren't kidding about the stalkers. Check out the bar chart at the bottom of the page:

https://deepmind.com/blog/alphastar-mastering-real-time-stra...

I guess it makes sense that the AI would favor such a micro-heavy unit. I imagine it would be a nightmare to deal with perfect blinking.




Dealing with perfect blinking is basically impossible, since you can blink back your units right before they die. Stalkers are balanced around the fact that HUMANS have limits to how well they can micro.


While the "skill cap" on blink stalkers is extremely high, there are many hard counters that can stop even perfect blink micro. MaNa won because he went for one these. Immortals are the perfect hard counter to stalkers because

- cost-for-cost, they are more efficient in a faceoff (resources)

- immortals are space-efficient dps (damage per second) in a battle. In a given battle, an army of 4 immortals is far more likely to all be in range of an enemy and doing damage than an army of 8 stalkers bumping against each other trying to get to the priority target

- immortal shots do not have projectiles, but are instant. No matter how perfect your stalker control, once an immortal targets a stalker, it is guaranteed to take 30+% of its hitpoints in damage.

The last point is very important. Once MaNa had 3+ immortals, even with perfect blink micro, a little bit of target fire and timing micro on MaNa's part allowed him to slaughter the stalker army one stalker per volley, while it takes them longer to clean up the immortals (especially with shield battery support).

Another thing glossed over in this discussion -- AlphaStar did more than classic blink micro. It did a very technical maneuver (the casters briefly allude to it) of triggering the barrier on one immortal with a single laser, then focusing all fire on an immortal whose barrier was already down from a previous iteration of this tactic, and then walking away until the barrier has worn off (while blink-microing weakened stalkers). Repeat. This is a detail of increasing the efficiency of trading stalkers with immortals that humans don't often even think about, let alone execute (because good blink control is often more impactful). That AlphaStar came up with this shows that it's not just about perfect execution of micro, but also perfect understanding of micro.


I'm also excited to see the future of this bot when they demonstrate a terran AI with near-perfect marine/stim/medivac micro.


Perfect micro bots don't excite me much, because they've existed all along, and it's not an AI task.


There was a "perfect zergling micro vs siege tanks" bot some time ago that would micro lings away from the one that was being fired at by the tanks, thereby negating all the splash damage. The effect was insanely powerful.

But as you say, showing that a bot can have perfect micro is not very interesting. Of course a computer can have better control of well defined tasks like moving a unit away just before it dies, especially doing so for many different units concurrently. What is interesting is the wider strategy and how the computer deals with imperfect information.


Here’s that perfect zergling video: https://youtu.be/IKVFZ28ybQs


The interesting part to me is that, as far as I understand, the AI figured out this strategy by itself, basically deciding that it would be a good way for it to win games, rather than being specifically programmed to do it. That's actually pretty cool!

Other than that, I agree, and am also much more interested in what happens when you have a more level playing field (using camera movement rather than API, limiting reaction times and CPM, etc). I look forward to future matches where this happens.


I think there is some debate about what the neural net did and what was hardcoded. So far all starcraft AIs consist of hardcoded intelligent micro ruled by a neural net that picks one out of less than 100 possible hardcoded choices. And things like "expand", "scout", "group units", "micro" are hardcoded outside of the neural net, part of the API in fact. When the researches said they only used 15 TPUs for 14 days on LSTM, this makes me think they really narrowed down the search space of the neural net and hardcoded a lot of the micro or at least trained separate micro nets.


Not really. The version which learned from scratch was scrapped as it didn’t work at all. This version learned by observing pros. So it didn’t learn by itself, it imitated and perfected pro players.


It was not programmed to do the thing, but all these tactics were in seed replays, from which the agent started its learning. So, it actually not figured the move _by itself_, only found it useful.


I'm scared. Medivacs only healing the front line and perfect stimming only the backline will be SOOO broken.




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