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AlphaStar: Mastering the Real-Time Strategy Game StarCraft II

• alextooter 8y ago
  I am as SC1 only player,hope someday there will be a SC1 AI player.
• z_open 8y ago
  They really should have used BroodWar for deep mind. SCII is way too volatile. Way more gimmicks available that will make it difficult for AI to come close to a human player.
  • TotempaaltJ 8y ago
    Why? They won ten out of eleven matches. Seems like they got pretty close to human players...
    • yifanl 8y ago
      The games it won, it had an access to inputs human players physically can't do (controlling units off-screen without panning the camera first), so I'm hesitant to call the victories legitimate. Edit: And reviewing the game it lost, the decision making was questionable at best.
  • briga 8y ago
    Isn't the difficulty of the task the point? If it was easy it wouldn't be interesting.
    • z_open 8y ago
      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.
      • sgarman 8y ago
        You should watch these replays, the AI is already way more advanced then the situation you just described.
  • kirrent 8y ago
    As much as I love brood war, great micro over a large number of units with wide awareness (things which appear to be easy to AlphaStar) would be ridiculously overpowered, even with completely average strategy. Brood War is an awesome game because it's constantly asking too much of its players at all times. I can't imagine games against an AI which has far more attention and micro to give would be too interesting.
    • z_open 8y ago
      They are planning on limiting the APM of the AI anyway. With BW, you can focus on an AI learning basic strategy with incomplete information. With SC2, you mix in a hole assortment of figuring out how crazy abilities like force fields and recall. It's going to take much longer for an AI to anticipate when its opponent is going to force field the ramp and warp into the main.
      • kirrent 8y ago
        I'm not really sure why you think Brood War is such a pure example of basic strategy without difficult to comprehend mechanics. Even in your example, recall is far crazier in Brood War. Arbiters can also create a version of a force field on a ramp that's uncounterable and lasts far longer. They're also harder to defend against because they have so much HP.
        • z_open 8y ago
          The fact that arbiters are stronger or weaker than the equivalent abilities in SCII isn't the issue. The issue is getting the AI tech to the point where it can figure out that you have to sac a base because it will waste time sending your army there only to have them recall is going to take a lot longer. An AI can figure out that there is an arbiter on the map, and that means there is a potential for it to recall some units into your base. That's easy. BW isn't the perfect example or pure strategy, but there are dramatically less game-changing abilities in it. Think cyclone/marauder cheeses or 2 base warp gate allins or ravagers seiging your wall. SCII in general makes attacks come quicker relative to scouting. Injects, chrono, and mules make tech and attacks come sooner compared to BW. Reliable scouting is still basically tier 2.
  • WhompingWindows 8y ago
    I had a feeling we'd see Brood War elitism in here. There are many, many gimmicks in BW. Every time I watch ASL and KSL, I see numerous quick stomps based on gimmicky builds, just like in SC2, Dota, and every other strategy game with fog of war and a collision of messy strategies.
    • z_open 8y ago
      Cheese isn't the same as gimmicks. I'm talking about abilities that change the game. There are more in sc2.
  • FlorianRappl 8y ago
    Thought the same - especially since afaik no AI has yet beaten a Korean pro. A few months (maybe 1 year ago) the best AIs tried vs some "retired" pro-gamers (like Stork) - it was not even close. Would have loved to see DeepMind trying to show what's possible here.
• minimaxir 8y ago
  How did they make those data visualizations? (specifically, the visually-skewed ridge plots). That's a nice approach for those types of plots since they can get cluttered without the perceptual skew.
  • b_tterc_p 8y ago
    https://seaborn.pydata.org/examples/kde_ridgeplot.html https://seaborn.pydata.org/examples/kde_ridgeplot.html I would try with a Seaborn facet grid? I think they’ve got something custom, but this should get close (be aware this specific example is a kde so it will normalize total area) On a second glance this won’t get the 3D horizontal offset.
    • minimaxir 8y ago
      A lot of the viz styles seem close to ggplot2 which is why I though it was made using ggridges (https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html https://cran.r-project.org/web/packages/ggridges/vignettes/i...) but I'm not sure if you can do a perceptual skew in ggplot2.
      • jon-wood 8y ago
        It wouldn't surprise me if they generated graphs and then handed them off to a design team to trace and make pretty.
• lettergram 8y ago
  So... I’m curious how long this will be before we can apply this to real life? At this point it seems like it’d be fairly complicated, but you could build a solid simulator for battles. Then direct humans and / or robots around the battle field as nessecary to win a battle. Upload a virtual map utilizing some point clouds, estimate densities, start with estimating enemy combatants, add some scoring metrics negatively impacting civilian deaths and probably a lot of other stuff. Run real life scenarios in training environments, and bam. The premise seems there.
  • civilian 8y ago
    There are a lot more variables that need to be added to for an "AI general". - There needs to be a system for simulating real-world battles. (Since we need to iterate the AI, afterall.) In WW2 the WATU was a good simulation of German submarine vs. Allied Convoy battles, but I imagine that ground battles are messier. Link for background: https://www.youtube.com/watch?v=fVet82IUAqQ https://www.youtube.com/watch?v=fVet82IUAqQ - Autonomous directions. If a unit loses contact with the AI, what orders should they follow? - Need to react quickly to changes in the effectiveness of weapons. If army-B has a Surface-to-air missile that has a 80% hit rate, rather than the estimated 40% hit rate, the AI needs to adapt. - Different armies have different tolerances for causalities, both military and civilian. I suspect you're getting downvoted because people don't like the idea of military-general AI. I don't really love it either, but it's going to happen. Hopefully we can encourage its programmers to include the Geneva convention rules for war.
• modeless 8y ago
  AlphaStar interacted with the StarCraft game engine directly via its raw interface, meaning that it could observe the attributes of its own and its opponent’s visible units on the map directly, without having to move the camera - effectively playing with a zoomed out view of the game Additionally, and subsequent to the matches, we developed a second version of AlphaStar. Like human players, this version of AlphaStar chooses when and where to move the camera, its perception is restricted to on-screen information, and action locations are restricted to its viewable region. I was really curious whether they would attempt moving the camera like a human. Sounds like it's still a work in progress, but very exciting! Even this isn't enough to make it fully like a human player, as I believe it is still getting numerical values for unit properties rather than having to infer them from the pixels on the screen. But it seems possible to fix that, likely at the cost of drastically increasing the training time. The benefit of using pixels, of course, would be that the agent would become fully general. It would probably immediately work on Command & Conquer, for instance, while the current version would require deep integration with the game engine first. But I think the training time would be impractically long.
  • aerovistae 8y ago
    yeah I was disappointed to discover it worked this way. don't get me wrong, it's a major accomplishment in AI regardless, but it's a significant advantage and it would be easier for me to appreciate the AI's skill if I didn't have to keep reminding myself that it can see the whole map at once. it's such an information advantage.
    • shawnz 8y ago
      It sounds to me like, although it could see the whole map at once, the fog of war was still applied. So the bot really just got as much information as the minimap would normally give a human player. > it could observe the attributes of its own and its opponent’s _visible units_ on the map directly
      • aerovistae 8y ago
        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 it all simultaneously. The computer can see the state of two health bars on opposite sides of the map at the same time, or 100 healthbars in a hundred places at a time. A human cannot do that, and even trying to move the view around fast enough to do so would render it impossible to actually do anything else. 3. If it's true that seeing more at once is not advantageous, then it must also be true that seeing less at once is not disadvantageous. So by that reasoning a player playing on a 1 inch x 1 inch screen would not have any disadvantage, since after all they're getting just the same amount of information as long as they move the screen around enough! Reducto ad absurdum, a player with a 1 pixel x 1 pixel screen has no disadvantage either, because they have access to the same information as long as they move around quick enough. It quickly becomes evident that smaller screens inhibit your knowledge of the game state, and therefore larger screen benefit your knowledge of the game state.
• cellis 8y ago
  I would really like to see this for Age of Empires II. I think AOE has far more races and is a far more complex game ( although I'm biased because I haven't played SC2 as much as AOEII ).
  • lucidrains 8y ago
    I'm sure that once the dust settles, we will have an AlphaZero version for AlphaStar as well
  • aerovistae 8y ago
    Same, totally agreed. I'm a really experienced competitive AoE2 player (not pro, just a serious casual), and I think the long-term planning inherent to AoE is far more complex than SC. Not to mention the procedurally generated maps that are different every game-- it's far more nuanced in my view and requires a truly vast amount of knowledge to make good decisions. There are so many different valid approaches to any given situation.
  • ascar 8y ago
    I haven't played AOE for ages, but aren't the races only different in a few details like 2 units and some passive effects? In StarCraft races are vastly different. I can't really judge AOE's complexity, but from what do you draw your conclusion? Just based on the number of rules?
    • cellis 8y ago
      Each civ (race) has about 2 different bonuses (e.g. Indian villagers work faster) and in addition a unique unit. Competitive players now play with about 20 civs. Each civ also has a "team bonus" (e.g. Teams with a Spanish player get 33% more gold per trade trip, teams with a Persian player get upgraded buildings ). In addition to that, each civ has a different tech tree, as well as starting resources or -- in rare cases -- starting units.
  • justfor1comment 8y ago
    I have played both games and a fan of both. Starcraft is definitely more complex than AoE for AI development and that's why the researchers must have chosen it. The complexity of AI depends on how many potential decisions you can make at any point of time. Here are a few reasons why: 1) Starcraft races have completely different build trees and different advantages. This has a large cascading effect of early decisions in the game. 2) Starcraft has much more micro potential that AOE. There are many units with sort of super powers like Stalkers can teleport and infestors can take control of enemy units. In AOE, you can only issue attack commands to most units. 3) Variety of units. Since Starcraft also has air units which may or may not be able to attack ground units, you have more options within a race to create a unique army/air force combination. 4) The Starcraft map terrain is hierarchical whereas AOE happens on a flat map. There are interesting locations on the map where a smaller army may be able to defeat a larger army based on positioning.
• integricho 8y ago
  I didn't catch if they mentioned this in the interview, but what would have happened if they let AlphaStar play against other races, not Protoss only, would it be completely lost, unable to achieve anything?
  • aerovistae 8y ago
    Good question. What's important, I think, is to remember that this is an early iteration, and regardless of what it can do now, they will continue to improve it and in a year or two or three (probably less) it will be able to play totally unfettered in all conditions.
  • modeless 8y ago
    The current version would flounder because it has never seen the other races. But that is not a fundamental limitation. All it would take to fix it is more training time.
    • dmurray 8y ago
      Or they trained all the combinations but it was best at Protoss vs Protoss, so they publicized those results. But given the reaction to the first AlphaZero announcement and the later follow-up paper (summary: they cheated a bit but it's still incredibly strong) I would give them the benefit of the doubt here.
• Thaxll 8y ago
  The problem is see is the AI is not better than the human, it's just 1000x faster at APM / macro. It could have a "shit" bo and still win because it's so much faster than a human. It's not really interesting tbh.
  • aerovistae 8y ago
    Wrong. Did you watch the presentation? Its APM was less than half that of its human opponent. If you aren't going to watch the presentation first, don't try to get involved in the discussion in such a derisive and dismissive way. "It's not really that interesting tbh"....wow. It's something that's never been algorithmically done before, no matter who tried. How can you write that off as "not interesting" as if it's totally insignificant?
    • Thaxll 8y ago
      I watched it and it doesn't means anything, they said it has lower APM than a human, but what an APM means for a computer anyway? APM is just a way of mesuring how fast you click on a mice / keyboard, but the descion making is not related to the APM speed. My point is it could click 10x slower than a human and still out beat it at macro. The real issue I have here is the game can be won by just outplaying the other at macro. Edit: They actually say exactly what I just said: These results suggest that AlphaStar’s success against MaNa and TLO was in fact due to superior macro and micro-strategic decision-making, rather than superior click-rate, faster reaction times, or the raw interface. It feels like bruteforce not really AI, that's my point. If a computer knows everything about the game ( mvmt speed, projectile speed, ect ... ) how it is you call it smart where it's just computing power to know when to engage and when not.
      • aerovistae 8y ago
        ....but.....but...that's EXACTLY the challenge of RTS games.....no AI has been able to beat a human at macro until now. That's the whole point... > was in fact due to superior macro and micro-strategic decision-making That's exactly the crux of the accomplishment! How are you writing this off as not impressive?! Like, what exactly do you want the AI to be able to do if not win by superior strategic decision-making?? > how can you call it smart when it's just computing power to know when to engage and when not. But it ISN'T just computing power, any more than AlphaGo was. If it was, then they would have already done this years ago, wouldn't they? Anyone could just rent some servers off AWS and do it. it isn't even remotely that simple. It's a major work of algorithmic innovation, and you don't seem to understand that.
• ascar 8y ago
  It's amazing what they achieved so far, but I wonder how it would stack up against Serral, who draws a lot of his wins by supremely judging an engagement and continiously gains small advantages over the course of a game. This is a skill even most other professional players only have on a much lower level.
  • cjbprime 8y ago
    Yes, a best of 9 (?) match against Serral or Maru needs to happen.
    • sabas123 8y ago
      But only if they get material to prepare with
• jonahx 8y ago
  Does anyone know if this opens the door to using these techniques for poker (given that they've now show success on games of imperfect information)? Thus far the solutions to poker have involved solving the game tree through raw computational power and clever methods of information collapsing: http://science.sciencemag.org/content/347/6218/145 http://science.sciencemag.org/content/347/6218/145 But it seems the techniques used here might be both far more efficient, as well as able to better exploit human players (as opposed to playing a pure game theoretically optimal strategy, which is what they do now).
  • b_tterc_p 8y ago
    Probably not. The AI demonstrated today was shown to be exploited with a strategy that wasn’t especially devious. It’s good at core mechanics but not strategically clever. I would bet on the optimal strategy over this one.
  • tialaramex 8y ago
    So, your link is about Cepheus. It's important to understand that Cepheus isn't AI, it's an (asymptotically close to) optimal strategy for Limit Heads Up ("Limit" means you don't need to choose bet sizes, they are fixed, which makes the problem much simpler), and since poker is a game of probabilities the strategy is probabilistic too. ie this is like when somebody explains Tic-Tac-Toe, there isn't anything interesting going on inside the machine, the insight was purely mathematical, that there are one or more optimal ways to play this game, and this is one of them. You can literally look at the strategy right now, you can do it while playing against a program that plays by this strategy. But you won't beat it by doing that, that's the point of this optimal strategy, the best you can do is play this or some other equivalent optimal strategy back, in a home game you'll just pass chips back and forth forever. In contrast Poker AI is a thing, and at _No Limit_ Heads Up the AI state of the art is clearly better than human, named Libratus - it is nothing like Cepheus, there is no fixed strategy. For "Full Ring", the game of Poker as you've probably seen it played, which has more than half a dozen independent players, AI would be very challenging, not least because if humans realise they're at a disadvantage it would be essentially impossible to prevent them from colluding with other humans to get an advantage, even to some extent unconsciously.
• kingbirdy 8y ago
  Very exciting results. However, I'm a bit confused by this graph [0], could anyone explain how I'm supposed to interpret it? 0: https://deepmind.com/blog/alphastar-mastering-real-time-strategy-game-starcraft-ii/#image-34385 https://deepmind.com/blog/alphastar-mastering-real-time-stra...
  • dfan 8y ago
    I was confused too; it has a weird format that I think hurts comprehension rather than aids it by making you think you're not looking straight at the data. Ignore the fact that the "Training Days" axis is drawn diagonally. The system is creating about 40 agents per day; by the end of day 14 it's made 610 or so. The graph shows, for any given time of training (vertical axis, going down), what is the distribution of trained agents that it's chosen in order to be unexploitable (you wouldn't want to choose rock all the time in rock-paper-scissors, for example). So, for example, at the end of day 14, it's using a selection of agents with numbers 595 through 610 or so, which means they've all been created within the last day.
    • ionforce 8y ago
      I think it's to help illustrate the time dimension as going forward rather than something that goes up and down. And also to not measure the hills against some global X-axis. It is confusing.
  • deleted 8y ago
    [deleted]
• AmericanBlarney 8y ago
  It's certainly interesting but reminds me of DeepBlue playing Jeopardy against humans but having nd the questions fed to it electronically. Half the challenge of the game is buzzing in first. For humans, requires reading/listening and potentially making a judgement they you'll be able to answer the question and buzzing in before even hearing the whole thing. Same thing for StarCraft. If I could nap out my movers in advance and feed them to the API with precise timing, I think I could likely beat a lot of pros - all the strategies mentioned a in the article are well known. The dexterity and timing are a huge part of the challenge.
  • doktrin 8y ago
    > reminds me of DeepBlue playing Jeopardy Apologies for the nitpicky correction, but that was Watson.
  • chc4 8y ago
    They mention that the latency of the neural network, from input to action, is around 360ms, which is on the lower end of professional level. It can do context switches between micro/macro very quickly, which is where it's strength lie, and it did some very impressive micro in the later matches against MaNa, but it didn't win solely off the back of "computers are fast".
• ctoth 8y ago
  Every year or so we get another huge advance... Well, more accurately, something comes along to benchmark the state of AI research against a human activity. Then come the HN comments. For Alpha Go: Oh this is impressive but can't generalize. Wake me up when it doesn't have to have information precoded/doesn't learn from human players For alpha go 0: So this is cool but not amazing because they're all perfect information games. And now here we have this, and people who haven't even watched the presentation are yammering about stuff like the APM, or how this isn't impressive because of ... Well, something? If I believed in a terminator scenario, I would point out that a robot, too, will presumably have higher APM than all of us desk warriors. It really feels like there are just some people who are religiously attached to being the only known intelligent entities on the planet, to the point where, when presented with evidence that hey, this is actually a thing, they will stick their fingers in their ears and shout about how unreal/unfair it all is. I invite you to have a look back at the other announcement threads from Deepmind and OpenAI. I decided not to directly quote people as I don't want this to get personal, but I couldn't just sit here and watch the same old story play out again without at least mentioning that these same people have been wrong, and wrong, and wrong, and will presumably continue to be wrong. Exponential curves are unintuitive.
  • noir_lord 8y ago
    I've heard what you said more pithily put as "true AI is anything we can't make a computer do right now".
  • scarmig 8y ago
    What does it matter, at this point? The proof is in the pudding, and we are making more and more pudding everyday. Instead of caring about naysayers, we need to be working under the assumption AI is here to stay and rapidly expanding in scope, and we need to build the social and political structures to be able to handle it.
    • setr 8y ago
      >we need to build the social and political structures to be able to handle it. This would be a massive waste of resources depending on how far you misinterpret the nature of the “AI thats here to stay”. There is little to support that we’re near-approaching a general purpose, “true” AI, the kind of superintelligent, creative, potentially world-ending and self-improving thinking machine that brings us to the singularity. Its much fairer to characterize current technologies as an algorithm that excels in certain fields, with distinct limitations that we’re still exploring, and have some idea but not perfect of where those limits are. Functionally, they just find probabilities matrixes for a certain sequence of actions, and can search the problem space much faster than we did before, by simulating the event indefinitely. And they come with the issue that anything that can’t be well-simulated and quickly can’t be “AI’d”, as well as the common issue of catastrophically failing due to not actually understanding the object in total (eg change a picture of a cat to an ostrich by editing key pixels). And afaik, they’ve shown no ability to “change the problem”, a key component of creativity (if you can’t find a good answer to something, consider changing the question; our “AI”s do not.) And this is naturally why they excel at games (almost by definition a repeatedable simulation) that typically have a very well-defined question. But at the same time, we don’t expect current AI to be capable of taking its “strategies” forward to the next update of starcraft (the problem changes) without re-searching a lot of the problem space (there exist algorithms for training future networks; I don’t know how much progress they’ve made), because they don’t really have strategies in the first place, or a real model for how things interact (they struggle to predict new interactions without sinulating them, or rather, “experiencing” them). Which is also why its difficult to imagine AI’s will ever truly be driving cars around with the current tech — rather, they’ll succeed likely as an awkward combination of nueral networks, expert systems, hueristics and safeguards. We’d naturally expect most sci-fi usecases of AI to be the same — eg political decision making. And they’ll be limited to the extent that we can render simulations. And if we pretend these distinctly limited algorithms are in fact the predecessors to our post-singularity successors, simply because they’re able to do a few things we weren’t really expecting (just as computers have proved to be a whole lot more capable than the 60’s general population thought, but far less than what 60’s scifi thought), we’ll do a whole lot of work for quite a bit of nothing. The fact that its called AI doesn’t mean we’re quickly approaching star trek’s Data AI. It didn’t mean it in the last few AI hype cycles either.
• tomc1985 8y ago
  These developments sound wonderful but all I can think about is how this advanced AI is going to used to try to control me (mostly my spending and consumption)
• rcheu 8y ago
  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 to be above what's physically possible, especially in the game against Mana where they were fighting in many places at once on the map. Human players have attempted the mass stalker strategy against immortals before, but haven't been able to make it work. The decisions in these fights aren't "interesting"--human players know what they're supposed to do, but can't physically make the actions to do it. While they have similar APM to SC2 pros, it's probably far more efficient and accurate so I don't think that alone is enough. For example, human players have difficulty macroing while they attack because it takes valuable time to switch context, but the AI didn't appear to suffer from that and was extremely aggressive in many games.
  • cm2012 8y ago
    In the showmatched they made the computer have to look at a regular screen to control, the stalker micro was much less impressive - and mana won.
    • Jyaif 8y ago
      The AI lost because it completely messed up the response to the immortal drop, nothing to do with micro.
      • celeritascelery 8y ago
        Mana got himself in the same situation where he was surrounded by stalkers on multiple sides, but this time the micro wasn’t so crazy that he couldn’t manage it, and he was able to take on one group at a time. The immortal drop, while unanswered, was not really that effectual.
        • setr 8y ago
• knicholes 8y ago
  You can download the replays here: https://deepmind.com/research/alphastar-resources/ https://deepmind.com/research/alphastar-resources/
• hughzhang 8y ago
  This is really impressive. Even though the camera hack / uncapped APM limits (only the average was capped) made this version slightly unfair since the ability of an AI to micro insanely well with stalkers is basically unbeatable, I feel confident based on this performance that Deepmind will release a superhuman AI with lower EPM than humans very soon from now.
  • Nanocurrency 8y ago
    I think it's "a lot" unfair. Waiting anxiously for the next version which will carry more limitations.
• olliej 8y ago
  The gameplay was really interesting - i wonder if we'll start seeing the over-saturation of the main prior to first expand in pro games?
  • ionforce 8y ago
    There are three things this seems to do. And what's changed is the perceived value of these. 1) Increased mining rate. Although there's a prescribed "maximum", as I understand it adding more workers, up to some limit, does yield more minerals beyond the prescribed. 2) Buffer against harassment. If you are over-saturated and lose two probes, you rate of income isn't affected. 3) Bootstrapping an expansion. All of the excess probes can be moved over to the new expo.
    • olliej 8y ago
      Right, I get that it AlphaStar has decided this is sensible, I just wonder if we'll start seeing pros adopt something similar? I'm also more generally curious as to what the cutoff point at which adding an additional probe ceases having any value.
      • cjbprime 8y ago
        My vague recollection is that from 16 to 19 workers the 17/18/19 worker is still harvesting >50% of a <16 worker, from 20-24 it's more like <25%, and the 25th worker onwards contributes 0.
    • schwurb 8y ago
      I read that AlphaStar might be able to play this strategy because it is really confident in its defense skills. For humans, that might be taking a risk that is too big. That said, I want to try it out anyway :) Edit: I recall that Rottie or someone said that there were 1-2 rare situations in HOTS where pros played like this.
    • lodi 8y ago
      Here's exactly how the mining mechanics work in sc2. 1) only one worker can mine from a mineral patch or gas geyser at a time 2) workers phase through each other while mining, so they don't lose time pathfinding around fellow workers. 3) every base has 4 "close" mineral patches and 4 "far" mineral patches. The close mineral patches are mined at full efficiency by only 2 workers; as soon as one finishes mining, the other has already returned and starts mining immediately. For the far patches, when one worker finishes mining, the second worker is only halfway to the minerals. Sticking a third worker on a far patch can cover that little mining gap, but the benefit is small (like ~30%). 4) therefore for efficient mining you want 16 workers on minerals. For "perfect" mining, you want 20 workers on minerals with the extra 4 on far patches only. 5) usually a triple-stacked close patch will automatically lose the excess worker to a far patch, but sometimes you need to "worker stack" manually to achieve this. You can see MaNa worker stacking manually at the beginning of his showmatch when he doesn't have anything else he could be doing with his excess apm. 24 workers on minerals guarantees maximum income because 4 workers will never fit on a patch; they'll start automatically reassigning themselves to different patches until they find a less crowded one. 6) more than 24 workers on minerals provides exactly 0 extra income. Still good to have extra workers though so you're not losing mining time when you build buildings, get harassed, etc. 7) every base has 2 vespene geysers, and 95% of the time these are in a position where 3 workers will saturate them perfectly. There are a couple of maps (or at least used to be... might be fixed now) where you can eke out the tiniest bit of extra gas by having 4 workers on a geyser. 8) every serious sc2 player already knows all of these mechanics I personally think Artosis was overstating the innovation of DeepMind's worker over-saturation. I agree with something Rotty said earlier in the series; sometimes you make a suboptimal move and it works, but that doesn't mean it was the "correct" play. It just means that you papered over a flaw with stronger execution somewhere else. I'm still very impressed with these games, just not with regards to the AI's build orders.
• ForrestN 8y ago
  Can anyone who has a full context compare this to OpenAI's work on Dota 2? Which is more impressive, both in how far along it is and the relative game difficulty?
  • ionforce 8y ago
    This feels more impressive since in SC2 you can pilot many units while in Dota you only (generally) have one. And Deepmind is playing (albeit a slightly older) stock StarCraft II while OpenAI had to play using a very weird ruleset (invulnerable carriers). Milestones that we have yet to see with Deepmind - generalize on maps - generalize on races - zero-style training
  • b_tterc_p 8y ago
    They’re probably comparable and at similar levels of success. Talking about which game offers more entropy isn’t a good metric yet because neither AI seems to be trying to utilize the depth available to them. E.g. the Dota game had 5 AI working as a team. That feels like it should demonstrate additional competence, but it’s not really clear that they worked as a team. The Dota game allowed greater variation in starting conditions, but it’s not apparent that the Ai adapts it’s strategy to this well (e.g. hero choice). Both of them are capable of creating a basic strat and excelling at micro. Neither appears to have great depth of strategy.
  • hughzhang 8y ago
    Starcraft II pros are probably much further from perfect play than Dota2 pros (simply because the game is harder). As a result, having perfect micro is a much larger advantage in Starcraft than it is in Dota 2.
  • glun 8y ago
    Dota is a much harder game strategically, in Starcraft it's easier to compensate with mechanical skill. You can see this in the results. The Dota ai played a very dumbed down version of the game and still got trashed by the pros.
• abakus 8y ago
  Hey, but isn't TLO a ZERG player?
  • pisarzp 8y ago
    He is, he played off-race, that's why they invited MaNa to allow AI play against very strong protoss
  • FlorianRappl 8y ago
    Warmup opponent:) They did the same with AlphaGo back then. First get some "good" player in there to see if they are on the right track. Then get a better player in there. Finally, prepare for a real showdown. In this case it would be ShowTime, Neeb or even some Korean pro (e.g., Stats). Maybe its time to switch matchups and make it PvZ - get Serral and then let's see if the current SC2 champion is good enough to beat this AI.
• karolist 8y ago
  I'd love this to be released for Company of Heroes (Relic), the game has terrain that effects engagements and vehicle movement, multi directional cover, individual model health in squad units, territory control based resource income and tick down win condition and much more that makes it feel more tactical than SC overall. It's got a bit of randomness where engagements are not just pure deterministic math inputs so I guess that's why it never gained pro league attention but it would be hell of an interesting challenge for AI because of it.
• SubiculumCode 8y ago
  It would be interesting to see a match of [human controlling macro while computer handled micro] vs [computer controlling macro and micro]. I haven't played the game.
• stared 8y ago
  Now, waiting for AlphaStar with Has (the cheesiest professional Protoss player, see: https://www.youtube.com/watch?v=AgxOV1L3Jl4 https://www.youtube.com/watch?v=AgxOV1L3Jl4).
• jaredtn 8y ago
  I'd be interested to see its hierarchical strategy and planning, especially across such a long timespan. Does anyone have any good references for similar hierarchical planning work (Feudal Networks, etc.) to look at?
  • gwern 8y ago
    It doesn't use hierarchical approaches at all, apparently. Just flat Impala with LSTMs and CNNs every tick.
• ChuckMcM 8y ago
  Because that is what we need to teach AI to do, build bases, extract resources, and build units to go out and kill everything else on the map :-) It is an impressive result, it seems pretty clear to me that as a force multiplier for developing decision tree software this technique works faster and more effectively than the waterfall techniques, and it gets better post release. But beyond the game theoretic applications I am still looking for an application where it reliably creates a better back end code generator for a new architecture faster than a person can.
  • pdimitar 8y ago
    I think the first ever applications of a more generic AI will be in corporate and military anyway, so yeah, the AI will build bases, extract resources and send security units to kill everything else on the map indeed.
• FlorianRappl 8y ago
  While this is super impressive we should not forget - it was just a single matchup (1/9, requires a lot of adaption; especially on the three races) on a single map (1/N, granted in SC2 the maps are not as diverse as in the original StarCraft) using a single (outdated) patch. Humans are still master in knowledge transfer playing an unknown map and lesser known matchup with greater precision. Once an AI reaches a level where knowledge is transferred more efficiently than what we are capable of I will start getting worried - not beforehand.
• akeck 8y ago
  "Next we'll demonstrate AlphaStar controlling real military units in Syria..." :-/
• RockofStrength 8y ago
  If they don't cap the apm at 300 or so, this means nothing. I am not impressed with super speed, only decision making matters. Deepmind, you can do better.
  • a_imho 8y ago
    AlphaZero was set up against Stockfish similarly on unequal footing.
• ValleyOfTheMtns 8y ago
  Impressive, but there's a couple of things I'd like to see them try one day. Plug AlphaStar into a robot that physically interacts with a keyboard and mouse to control the game. This "robot" should only have what's relevant for playing the game and emulates a human i.e. a camera that looks at a screen (this is the only knowledge it has of the game), and two arms & hands with five digits that control the mouse and keyboard. Then limit its APM to the best a human can realistically do. The other thing I want to see them address is the virtual training time. 200 years of StarCraft is insane. LiquidMana has been playing for ~20 years and of course he hasn't played the game 24/7. Lets pretend he has played StarCraft like it's a full-time job since he was 5; 8 hours a day, 5 days a week, for 20 years. That's ~42,000 hours of playing StarCraft. Develop an A.I. that is only trained for that many hours of virtual game time. If they can create an A.I. with those requirements, that can defeat top-level players, I will be completely blown away.
  • gpm 8y ago
    Human pro gamers have sevaral advantages that mean they should need slightly (but probably not that much) less game time. Transfer learning from the rest of life, games are designed to be understandable to humans with familiar concepts, that AIs don't start knowing. Discussion with other players. Mana benefits immensely from every else's 20k hours of SC2 as well. Selection bias, there are many many people who try SC2, only the people who are naturally good at it succeed. So in some sense we need to be counting the rejects training hours as well. I would like to see advances on training AI using less data. I just wanted to comment that the comparison in number of hours isn't quite fair.
    • ValleyOfTheMtns 8y ago
      Those are really good points.
• infogulch 8y ago
  Many comments here are about how the AI information advantage (seeing the whole map at once sans fog of war except the last game; seeing exact unit stats like health etc) leads to higher APM-value, whether APM itself is higher or each Action is more meaningful, and discussing different ways to nerf it to bring it down to a human level. I'm more interested in the limits that an AI could be pushed to vs humans, and if humans can't match the AI's APM, just add more humans until they can. E.g. 1v7 would allow humans to manage multiple disparate flanks at once just like an AI, and still leave someone to free to manage macro play etc that suffers when a human focuses on micro.
• alasdair_ 8y ago
  What are the games that, so far, still look like they will be too difficult for ML to play them at the highest level? I know Go was held to be this kind of game for a long time and is now close to being dominated by AI. Magic: the gathering perhaps?
  • cjbprime 8y ago
    I don't think there are any left. No Limit Hold-em would be my next choice after SC2 but the bots are doing fine there too.
  • anabis 8y ago
    non zero-sum games seems like a logical next step.
    • jabl 8y ago
      Any (reasonably) popular games that are non zero sum?
• owens99 8y ago
  Interested to hear what others here think. The APM metric includes all clicks a player makes. AlphaStar's APM is lower than a typical pro's, but that does not mean it is making fewer actions. All pros try to keep a high "tempo" by constantly clicking the screen even when they are not making any actions. e.g. Instead of sending a unit to a specific location with one click, they will click 5-6 times while dragging the mouse to that spot. The theory is that keeping a high tempo allows you to make more useful actions overall. Unless AlphaStar's average and maximum APM is 3-4x lower than a pros, rather than just 2x lower average and the same maximum, I do NOT believe that this is a fair test of the AI's strategic decision making ability.
  • owens99 8y ago
    I also wanted to note that the millisecond response time performed by AlphaStar also seems an unfair test. While the average was around 350ms, this number is skewed by a significant long tail extending up to 1300ms for some actions. The most common response is sub-200ms and the third most common response is 65ms-100ms. The best pros can consistently hit close to 200ms but I am not sure if they can even hit below 100ms, let alone 65ms.
  • sabas123 8y ago
    In the starcraft scene we have terms to describe what your saying: you have APM and EAPM (effective APM). Historically the fastest players were around ~230 eapm and that was considered godlike.
• arnaudsm 8y ago
  Today, 1/1 games without the camera hack were won by the human. This is disappointing, but their PR is a success. Mainstream media is already saying "AI has beaten StarCraft". Another lie for the AI bubble I guess.
  • ehsankia 8y ago
    It's not "games", as it was a single game, and it came with the big caveat that they didn't have much time to actually prepare and train this one as much. The one that won against Mana was trained for 2 weeks, versus this one that only had one week of training. While the AI did have an advantage in terms of micro/camera view, it still was able to make decent decision making and independently come up with a bunch of interesting strategies. At the end of the day, that's really the goal of the research, not whether or not it uses the right number of APM or uses the camera properly. Those are just artificial restrictions put to make it look fair and entertaining.
    • arnaudsm 8y ago
      I would love DeepMind to put that AI on the ladder as they discussed during the last Blizzcon. The APM and camera restriction is not for entertainment, it's to develop intelligence rather than 1500+ APM. The interesting part of StarCraft II is decision making and the meta of the opponent, and we didn't see that today. Remember their Dota2 bot that was beaten by a lot of players after a single day. I want to see if AlphaStar can really adapt to the real world, therefore the meta, the real challenge of StarCraft.
      • schwurb 8y ago
        I honestly do not think meta or strategy will be interesting in SC2. (Obviously as a player it will, but from an AI standpoint not). AlphaGo already showed us that it can handle strategy well; A good AI in SC2 will simply scout the minimaly needed amount of time to prepare the perfect responses.
• celeritascelery 8y ago
  Here is an example of what you do without artificial limitations on actions. https://youtu.be/3PLplRDSgpo https://youtu.be/3PLplRDSgpo Just goes to show how important those restrictions are for competitive gameplay against AI.
  • owens99 8y ago
    This is amazing. Thanks for sharing.
• rhlala 8y ago
  Trying to solve Imperfect information games is interesting. But realtime game is not. As computer have edges in boring fileds (apm etc). I feel the real challenge will be Imperfect information, turn based, and cooperation( teamplay based) for ai. Unfortunately there are currently no game AFAIK with these characteristics... Like a 2d turn based counter-strike or dota/lol would be really the good format game to solve.
  • sandov 8y ago
    Civilization?
    • kerbalspacepro 8y ago
      AlphaCiv would be interesting as hell, but I fear that there isn't historical data for Alpha to consume. I would expect it would have a similar result to AlphaStar though-- it beats the human player before the end game.
      • worldsayshi 8y ago
        Perhaps it should have other targets than simply beating the opponent. Like getting good statistics.
  • brianberns 8y ago
    I think some card games meet your criteria. Specifically, Bridge, Hearts, and Auction Pitch (aka Setback) are all complex, turn-based, imperfect information games with some amount of cooperation. I’d love to see DeepMind take on one of these games.
  • Veedrac 8y ago
    Competitive Pokemon with teambuilding would be something fresh I don't think existing techniques have figured out yet. Not super prestigious, but IMO still a good intermediate goal.
• confiscate 8y ago
  How does outcome prediction work? It sounded like that was based partly on Supply (Army size). But the AI only knows it's own Army Size, and not the human's army size. So how can the AI's outcome prediction be so accurate? At game 3 against Mana, the AI's outcome prediction changed from 60% win to 99% win, before the AI decide to go up the ramp. It had no way to know if the human had more army up that ramp
  • clickok 8y ago
    In imperfect information games (like SC2) the outcome prediction implicitly takes into account the unknown. Given what it has observed and what it has not observed, it is essentially comparing the present state to similar situations from the past. You can see this in the replay-- at seemingly random times, its outcome prediction jumps up, even when it hasn't had any interaction with its opponent. But that's precisely why it's going up-- it notices that its opponent has not executed a faster rush or cheese that it's unprepared for, hasn't expanded early, and the scout has not been destroyed. Similarly, after having won a fight, the worst thing that could happen is that a bigger force emerge from your opponents base, destroying your army and giving them a chance to rebuild. When that does not happen, you know that your opponent probably doesn't have such an army (because otherwise they are falling behind in resources due to being bottled up). Either way, after a certain point it's worthwhile to press on to cause more damage, because you're now far enough ahead in resources that you will win regardless if they manage to repel that particular attack.
    • confiscate 8y ago
      Yes but it seems impossible to manually assign a score to all those different situations? There are too many situations like that Is the outcome prediction score, itself, also produced by AI training? It has to be, right? Because it's clearly not just calculating the outcome based on Army Size of the AI and the human. There must be some non-direct way it's calculating the outcome prediction. I mean, the hard part is accurate outcome prediction. Once you have that, it's easy to train an AI by just throwing CPU's at the problem and making the AI play a crazy lots of games
• miguelrochefort 8y ago
  The first artificial Korean.
• m0zg 8y ago
  Man, I can imagine the militaries the world over are rubbing their hands in anticipation when watching this. Imagine a perfectly orchestrated swarm of UAVs dealing damage like this (potentially to another swarm).
• Questioneer279 8y ago
  200 years of blink stalker meta... Overcoming the local minimum trap is still a thing.
  • javier2 8y ago
    funnily enough, human players were also obsessed with blink stalkers for years ;)
• dev_dull 8y ago
  Here’s the question I have. Will it consistently beat the top player over and over? I see so much brittleness in AI such as this. Humans are much less prone to “bugs”. In an evolutionary adversarial environment, the human brain invariably comes out on top.
  • ionforce 8y ago
    That's not fair. Humans are incredibly fallible. Humans tire, demand food, need to sleep, get bored. An AI just needs a graphics card and electricity.
  • etiam 8y ago
    In the very long run it's hard to see that we could compete with arbitrary scalability and lightning fast operations. In present and imminent situations, I thing Louis Rosenberg had an exceedingly important point in "Artificial Intelligence Isn’t Just About Intelligence, but Manipulating Humanity: AlphaGo's true accomplishment isn't learning to play Go, but learning to play (and manipulate) us." (https://futurism.com/artificial-intelligence-isnt-intelligence-manipulating-humanity https://futurism.com/artificial-intelligence-isnt-intelligen...) , around the last AlphaFoo. "Imagine a flying saucer lands in Time Square and an alien steps out carrying the game of Go. He walks up the nearest person and says the classic line – “Take me to your best player.” Now, let’s assume that the alien spent years studying how humans play Go, watching replays of every major match. If that was the situation, it would seem Humanity was being set up for an unfair challenge. After all, the alien had the opportunity to thoroughly prepare for playing humans, while the humans had no opportunity to prepare for playing aliens. The humans would likely lose. And that’s exactly what happened last month when an “alien intelligence” named AlphaGo played the human Go master, Lee Sedol. The human lost in 4 out of 5 games. But, if we look at the big picture, it wasn’t a fair match."
• nopinsight 8y ago
  Fun observation on the possible reason why they chose Protoss from the publicity standpoint: Zerg — Too icky for some in the general public Terran — Too human-like. Might clearly trigger the imagery of human-robot wars.
  • fernandotakai 8y ago
    imho, the AI had a better time playing as a Protoss because of blink stalkers. you can probably perfectly micro marines + marauders + medvacs with stim, but it's a lot harder than blink.
• jgrowl 8y ago
  I wonder how useful ai will be in balancing games in the future. Games with more than one race and multiple upgrade paths seems like a nightmare to ensure that things are even for players that are equally skilled. It would be interesting to have a game that would auto-balance itself, especially if you wanted to add extra content without having to worry about throwing everything off.
  • forax 8y ago
    That's a cool idea but many games already struggle to find a fair balance point at all ranges of human skill, so expanding that range to include AI could just make things more difficult. Maybe there's a way to force the AI to replicate bad players, but I'm not sure what learning objective you would give it to achieve that.
    • skwb 8y ago
      I don't follow gaming balancing too closely, but I (naively) assume there's some reasonable analytical solution to find tuning. Like I would imagine if you're Blizzard and have logs of all the data, you could just regress race attack/defense/movement/etc. stats to find a potential equivalence point. I suppose there's lots of interactions, but finding "well Zerg beats Protoss X% of the time", you could balance by messing slightly with resources or blanket buff.
      • glun 8y ago
        Starcraft is generally balanced by adjusting the map pool rather than the races.
    • Etheryte 8y ago
      I think achieving suboptimal play can be pretty straightforward — keep the parameters the same, but simply limit the amount learning. Some tweaks might be necessary here and there, but as long as you have basic gameplay down but not perfected, it should work pretty well.
  • donmatito 8y ago
• bronz 8y ago
  i dont mean to be negative but ML and even conventional computing are starting to make me tired. im always wondering what it will be next that ML can do better than humans. what is next up for automation? will this be the one to send a shock-wave through an industry / the economy? i feel like i need to constantly watch and keep track of the progress thats being made. and im starting to get tired from having to re-think life again and again. for example, google has published voice synthesis samples, voices generated from text, that are indistinguishable from real human speech. it hasnt been perfected yet, but i think most people would agree that we basically now live in a world where voice recordings cant be automatically trusted the way they used to be. it completely changes the way you think about and navigate the world. it will open up a universe of new schemes, methods of fraud, etc etc that we will have to adapt to. then there are deepfakes. there are limitations, and the results arent perfect, but its very early days. again i would say that the consensus among us is that we now live in a world where video evidence is basically no longer intrinsically trust-worthy in the way that it used to be. i practically grew up inside a computer. but i am now sensing that as ML fills in, its going to be a very uncomfortable ride for me personally -- and i dont understand how it couldnt be for anyone else. and what about when AGI comes? just curious to see if anyone else shares my experience with this.
• potatofarmer45 8y ago
  APM is a really really misleading metric to use here. Most starcraft pros spam keys to keep themselves loose and ready when the time comes. Even at the start of a game, you'd often see players with 500 apm warming up the fingers. Here, there is the laughable graph of the computer apm over time. The key points here is that when there were the mass battles that won the game, the apm spiked to >1000. And if you look closely in slow motion, there was perfect split targeting. A human player wouldn't be able to perfectly select the exact number of stalkers to hit the enemy without wasting a surplus shot. They can, but not when it's mass stalkers. This efficiency is just beyond humans. The APM here indicates much more effective use of an action than a typical human. This is super impressive as an achievement, but this is clearly not a smarter ai, but moreso an ai like the video a while ago where zerglings could perfectly micro against siege tanks to avoid splash damage. It is clearly better than humans in certain ways, but not smarter.
• ddebernardy 8y ago
  This is really sweet. Any odds someone at DeepMind might be working on Paradox Interactive titles like Europa Uiversalis?
  • skwb 8y ago
    Do you know if there's a good API for paradox games? I have off the top of my head seen extensible mods for games, but I assumed they all were based off of the predefined Clausewitz Engine. That said, HOI4 could really use some AI love. Right now, I think the AI has a lot of hard coded values (when invasion should happen vs not). One of the potentially beautiful things about modern AI is that if you can clearly define your objectives, it's possible to find a parsimonious analytical solution to solve that problem. I have immense hope that these gaming AI systems will transform the way we game in the future.
• kriro 8y ago
  First Go, now Starcraft 2...I fully expect archery or women's golf to be conquered next. Someone at deepmind must have an axe to grind with Korea ;)
  • erikb 8y ago
    This is more about historical AI challenges. When Chess was beat people realized painfully and happily that they can't beat Go with the same approach. Therefore it was the new Mount Everest. And Starcraft is a competition because SC1 was a game that was easily adaptable for AI hobby coders and competitions. A little like they have this Robo Soccer world championship for Robo builders. It's part of the domain culture I guess.
• eecsninja 8y ago
  How I would summarize the development of AlphaStar and Mana's strategy over the series: 1. AS studies games played by humans to learn what they do. 2. AS takes advantage of high-APM, high-precision blink stalker micro to defeat immortals (something no human can cognitively/mechanically accomplish). 3. Mana realizes he cannot play vs AS as if he were playing vs a human. 4. Mana discovers an AI exploit using the warp prism + immortals to force AS's army back, keeping his own base safe. This is a specific counter-AI strategy, not something that would have worked vs a human player. AS does not know how to properly react because it has not seen any replays of humans going up against an AI by exploiting it. 5. Mana gets enough breathing room to build up a large enough force to win the game. In short, Mana won because he "solved the problem" of how to exploit this particular AI. This is actually not a new strategy -- several years back, the stock SC2 AI would do the same thing: pull back when you attacked its base. I could win vs AI using the exact same trick that Mana used. Blizzard has since updated the AI not to fall for this trick. The real test of DeepMind's learning abilities is thus: if AlphaStar had seen replays of that exploit vs AI, along with all other replays of humans vs AI over the years, would Mana still have been able to win?
• a_imho 8y ago
  This is from 2011 https://www.youtube.com/watch?v=IKVFZ28ybQs https://www.youtube.com/watch?v=IKVFZ28ybQs I will take this with a grain of salt.
• EGreg 8y ago
  I wonder how far AI can progress. Can for example five robots, built to have insane reaction times and agility, outperform and safely subdue an entire army of 1 million humans equipped with the latest melee weapons? Or how about a tiny flying robot with millisecond reaction times in a room with a crowd of people trying to catch it, being able to eg buzz and tag everyone without being so much as touched? How about one robot which builds replicas or otherwise organizes some massive “real time strategy growth” across a city, versus the entire city and its police and army being called in? With the robot swarms coordinating distributed superhuman strategies and timing? I feel that, whatever we are discovering now, aliens who make it to Earth will have had hundreds of years advantage on that. It seems Monte Carlo Tree Search is the best we’ve got against the aliens, for now. Think Ender’s game but for real. It will require something like that. Anyone also remember the narration in Edge of Tomorrow? There the aliens had the additional advantage of resetting the clock to the beginning thus nullifying any win, but really with trillions of games being played by a league against itself, that rare “restart” seems quaint versus what we have here. Or over eons perhaps long term strategy with mining asteroids with Von Neumann probes competing.
• donmatito 8y ago
  Ok now are we getting DeepMind vs OpenAI competition ?
• ece 8y ago
  I think Deepmind definitively showed the agents are learning high-level play, which was great to see. I didn't really pay attention to AlphaGo, but did skim the AlphaZero paper, and I'm not really left with any doubts about how good RL/LSTMs can get against other AI or humans given enough time to train. That said, it's an open question whether given all the constraints of the last live match and what was mentioned during the talk (that newer strategies keep getting discovered by humans and agents), whether humans could even win 50% of the time against an agent.
• dpflan 8y ago
  https://www.wired.co.uk/article/deepmind-starcraft-results-alphastar https://www.wired.co.uk/article/deepmind-starcraft-results-a... "In a final match against Komincz, streamed live on Twitch, the DeepMind team used a new agent that, unlike those in the other matches, could only see by moving the focus of the in-game camera. As a result, the AI was forced to move its units in a more focussed, human-like way. Despite dominating the game early on, AlphaStar lost. In all the games contested to date, the score is: AlphaStar 10 - Humans 1." I'm not quite sure I follow the test then. How was DeepMind making decisions before? In a less-human-like way?
  • Tistel 8y ago
    If I understood correctly. In the first 10 matches AlphaStar can see the whole map in detail (not just the mini map) at the same time. The humans can only see their camera's view. In the 11th match the AlphaStar can only see via a camera view as well. It has to move the camera the way a human would to see other parts of the map in detail. The 11th game was a fairer test. This, along with the documentary of the human go players vs the deep mind AI, seems to indicate we are entering an interesting time. The humans start out cocky, then gradually concede the high ground of whatever skill is supposed to be our exclusive domain. I think we will make it through to some new way of living with very capable machines. But, to transition there we are going to have some rough years. Just watching the Star Craft player's fingers flying at the end of the movie makes my carpal tunnel wrists ache. It reminds me of the folklore about "John Henry" trying to keep up with rail laying machine. TL/DR: In the story he beats it for a while, then falls over dead from the Herculean effort required to do so.
    • dpflan 8y ago
      Allowing the machine to have a far-more informed view of the game than a human seems like these tests are not realistic battles. The human should have the same information about the game as the machine. I would certainly hope a machine with more information than the human could beat a human. Perhaps I am not understanding the situation?
• etiam 8y ago
  "Along with the original title, it is among the biggest and most successful games of all time, with players competing in esports tournaments for more than 20 years." ... Dear Mister Language Person: I am curious about the expression, "Part of this complete breakfast." The way it comes up is, my 5-year-old will be watching TV cartoon shows in the morning, and they'll show a commercial for a children's compressed breakfast compound such as "Froot Loops" or "Lucky Charms, " and they always show it sitting on a table next to a some actual food such as eggs, and the announcer always says: "Part of this complete breakfast." Don't they really mean, "Adjacent to this complete breakfast, " or "On the same table as this complete breakfast"? And couldn't they make essentially the same claim if, instead of Froot Loops, they put a can of shaving cream there, or a dead bat? Answer: Yes.
• Layvier 8y ago
  I think there's a lot more to limit than average APMs and reaction time, in order to have human-like capabilities. For instance: - the context switching cost of multitasking - the precision/speed tradeoff : pro players adjust the mouse speed according to what they want. Selecting exactly the units wanted is very difficult, AlphaStar seemed to do it perfectly. - the timing precision of an action With restrictions such as these, I'm honestly confident that AlphaStar won't beat human players anytime soon (once the human players adopt the interesting findings of the AI). I'm mostly interested in how it will change the meta. Players are often biased by their experience, and regularly the meta shifts entirely without any significant balance update, simply by players finding original strategies
• crb002 8y ago
  I'm curious to see a StarCraft II mod where you can assign advanced micro behaviors to groups of units.
• ggggtez 8y ago
  There seems to be an impulse to deny the AI progress that people see in front of them. When IBM Watson won on Jeopardy, everyone claimed it was cheating because, after all, "everyone knows the answers, so Jeopardy is really only about who presses the button first". But what about the fact that a computer could know the answers at all, and so quickly? Many people didn't think it was possible, and as soon as it happens they attack the speed of the button press as if knowing the answer wasn't the hard part. Anyone with this point of view does not seem to understand what is being shown here. This is not just "this ai beat this one player in this one match". It's an entire system of techniques for machine learning. The AI was not hard coded to learn those micro steps, like all other AIs have been. To ignore those things is to miss the point entirely.
  • porpoisely 8y ago
    Exactly. It's not like the AI of the past where it was essentially flowchart plus heuristics. Now, it's almost "experiential". It's tries paths and essentially sees which ones work and which don't and "learns" from it. It's similar to Dr Strange in Avengers using the Time Stone to try out possible futures to see which ones work.
  • bo1024 8y ago
    I see your point and partially agree. But I think part of the problem with these kinds of stunts (for lack of a better word) is it's hard to tell the difference between actual scientific advancements and benefits of throwing hundreds of years of GPU time at it.
• En_gr_Student 8y ago
  And now they are superhuman with regards to "Fog of war"! A truly crushing next step would be to make "World in Flames" into a computer game, and have Alpha-Star-Zero, which is coming, to become the best it can on that. http://www.matrixgames.com/products/296/details/World.In.Flames http://www.matrixgames.com/products/296/details/World.In.Fla... If they do that, every single military on the planet should crap themselves, including the US, Nato, Russia, China, and EU. It means that 20 years or less to robots able to operate at every level in an army from soldier to general, and able to comprehensively defeat the best humans at it, at every level. The first nation to the battlefield with this wins the world. One ironic part is that an excellent application is non-battlefield warfare. You don't have to drive a tank to conquer the world; perhaps you can buy a factory or make a deal. The corporate interface here should also be compelling. Perhaps Alphabet will finally be able to use this to make non-advertising profits.
  • erikpukinskis 8y ago
    You are comparing formal systems, like Starcraft, where the entire game world is quantized, with the real world where the games are not quantized. Not only is the game of war not “written down” in digital form, there is far too much data to ever write down. Military strategists have been trying to model war forever. But no one can even agree on what the “game pieces” are, let alone list all of the Deus Ex Machina that might show up. An AI that is better than any human commander at tank warfare would have been just as dead as any human army when the opponent shows up with an H-bomb. But being good at tank warfare also isn’t anything like being good at a tank game. To be good at tank warfare you need to be good at building factories. Pouring concrete in swamps. Convincing grannies to buy fewer cans of beans, and eat more squash. Figuring out when your workers really need to go home and sleep. Part of the game is just realizing thosethings are even things you might want to think strategize around. And the nature of competition in real life is that as players gain advantages, opponents copy their skills and those advantages cease to work. Then you have to find new advantages in some aspect of the game that has never been documented before. In a sense, high level real world competition is more like MAKING games than playing them. It’s about designing a competitive landscape where your opponent won’t be able to design their way out of it. Something AIs haven’t, to my knowledge, even begun to be able to think about.
• grogers 8y ago
  When deepmind announced they were working on sc2 expected it to be good, but not this good. Compare this to the top bots in SSCAIT (a BW AI tournament) and it's already so far ahead of anything that's existed up to this point. I'm eagerly looking forward to them playing all maps and matchups, I suspect it should be relatively easy to extend to. They've still got a long road ahead but this makes me think they can do it. However, they keep harping on the APM being similar to a top human and it's just not. Maybe the average for a whole game is, but during fights it was bursting over 1500 APM with perfect execution. This wasn't just spam clicking corrosive bile or something like a human might to get that high but truly coordinated targeting and unit movement. This had lead it to use pathological unit compositions that wouldn't be effective for human play (like pure stalkers beating immortals). If they set a hard max APM to something like 600 I think it would develop more useful strategies.
• ENOTTY 8y ago
  I feel like this was a lost opportunity to play it centaur style, letting a human choose and play an overall economic strategy (macro) and let the AI do the combat (micro).