111–120 of 459 posts
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Isn't the difficulty of the task the point? If it was easy it wouldn't be interesting.
What's going to be uninteresting is when their AI can never get past bronze league because the AI can't figure out that his bunker is going to get force-fielded or that observer is going to be used for a blink all-in.
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No, not true. Just had an extended argument with a friend over this. Here are some of my arguments against what you're saying: 1. While it's true that a human player could see everything the AI is seeing, the human player has to spend time and clicks to go see those things, whereas the AI sees it all simultaneously without having to use any actions or spend any time to take it in. 2. Emphasis on the computer seeing i…
> whereas the AI sees it all simultaneously without having to use any actions or spend any time to take it in. Starcraft is a single-threaded game, so I would think that the AI ultimately still has to enumerate through each visible unit one-by-one to collect their information. Why is that so much different than enumerating through each visible screen and then enumerating through each unit on that screen? Either way,…
This is really impressive, I didn't expect starcraft to be played this well by a machine learning based AI. I'm excited to read the paper when it comes out! That said, I'm not sure I agree that it was winning mainly due to better decision making. For context, I've been ranked in the top 0.1% of players and beaten pros in Starcraft 2, and also work as a machine learning engineer. The stalker micro in particular looked…
"The AlphaStar league was run for 14 days, using 16 TPUs for each agent. During training, each agent experienced up to 200 years of real-time StarCraft play. "
MaNa probably played less than 2-3 years of Starcraft in his whole life (by that I mean 24hr x 365d x 3), and was learning with a much less focused/rigorous methodology.
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This is exactly what I think, I'd like to see how Alphastar react to "cannon rush" or other weird bo where you need to be "smart" to counter it and just not be based on insane / none human micro.
This is how it responds to cannon rush. : ) https://www.youtube.com/watch?v=vYdWQjTWTFM
This is really impressive, I didn't expect starcraft to be played this well by a machine learning based AI. I'm excited to read the paper when it comes out! That said, I'm not sure I agree that it was winning mainly due to better decision making. For context, I've been ranked in the top 0.1% of players and beaten pros in Starcraft 2, and also work as a machine learning engineer. The stalker micro in particular looked…
In the mass stalker battles, the AI APM exceeded 1000 a few times, and no doubt that most of that was precisely targeted. Whereas a human doing 500 APM micro is obviously going to be far more imprecise. I think a far more interesting limitation would be to cap APM at 150 or so, or to artificially limit action precision with some sort of virtual mouse that reduced accuracy as APM increased.
IIRC OpenAI limits the reaction time to ~200ms when playing DoTA2. AI employing better strategies than humans will always be more interesting than AI that can out click humans.
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Actually, I would say this might be the strength of AI from another perspective: the ability to observe and monitor global information without losing attention. Or in other words, attend to the whole picture from get go without being overwhelmed. While it is an unfair advantage in competitive gaming, but in more realistic settings, there is no requirement that AI needs to have only 2 eyes. It can have as many as it c…
While that would be amazing if true, I'm pretty sure if you take away the stalker blink micro AlphaStar loses hands down to humans. This isn't taking away from Deepmind's victory at all, but I think micro was what made the AI come out ahead in this one. In many of the games, Mana had much better macro only to lose to blink stalkers.
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Its APM maxed out at 1500apm which is far more than any normal human.
That's instantaneous APM, not general APM over the course of the game. The human player's instantaneous APM went well past 1000 at certain moments during the course of the matches, too. All that means is a few clicks as fast as possible.
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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.
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Also I wonder how it handles invisible units. Because as a human player you can see the shimmer if you look close. Can it see that or are they just totally invivisble to it?
Presumably completely invisible, as it was looking at raw unit stats rather than the visuals.
Or better yet, imagine zerg where you can burrow every unit.
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> whereas the AI sees it all simultaneously without having to use any actions or spend any time to take it in. Starcraft is a single-threaded game, so I would think that the AI ultimately still has to enumerate through each visible unit one-by-one to collect their information. Why is that so much different than enumerating through each visible screen and then enumerating through each unit on that screen? Either way,…
You can eliminate that advantage by letting the AI only see the unit information for things on screen, like they did in the last game.
Let me put it the opposite way: If you gave the human player a real time list of every visible unit on the map and all of their information, such that they didn't have to move the screen around manually and could see everything at a glance just like AlphaStar can, would that take the advantage away from AlphaStar? No, it wouldn't because AlphaStar could still go through all that data much faster than any human ever could -- no matter how it's formatted or what you have to do to access it. To AlphaStar, checking all the visible screens is just as much work as scrolling through a list of units.