I am tempted to take a peek at coding something myself.
BoxeR: "AlphaGo won't beat humans in StarCraft" - Page 21
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Hotshot
Canada184 Posts
I am tempted to take a peek at coding something myself. | ||
LetaBot
Netherlands557 Posts
On March 25 2016 08:19 Hotshot wrote: That is interesting. I watched a game from 2015 bot vs a russian pro gammer... Looked interesting, but I felt I could definitely code something better/stronger if I invested enough time. I saw so many AI things that bugged me. I am tempted to take a peek at coding something myself. http://www.teamliquid.net/blogs/485544-intro-to-scbw-ai-development | ||
Musicus
Germany23570 Posts
https://www.reddit.com/r/starcraft/comments/4c4vqr/from_wcs_shanghai_tim_morten_confirms_that_the/ Might actually be sc2 instead of BW though. | ||
mishimaBeef
Canada2259 Posts
Go, check. Starcraft, incoming ![]() | ||
mishimaBeef
Canada2259 Posts
Wow, if that ain't confidence I dunno what is. | ||
Nebuchad
Switzerland11913 Posts
On May 26 2017 21:52 mishimaBeef wrote: "Google is reportedly considering using a robot arm for its AI in order to even the odds with a human who will have to use a keyboard and mouse during the match." Wow, if that ain't confidence I dunno what is. I mean if you have infinite APM and as such absolutely perfect splits can't you MarineKing your way into every TvZ with minimal intelligence? | ||
mishimaBeef
Canada2259 Posts
"Players have praised the technology’s ability to make unorthodox moves and challenge assumptions core to a game that draws on thousands of years of tradition." "This time, Mr. Hassabis said, a new approach allowed AlphaGo to learn more by playing games against itself." | ||
mishimaBeef
Canada2259 Posts
If the AI can play games against itself in Starcraft, it can probably do so at blazing speed as well (x16 replay speeds? still might be a snail's pace given modern microprocessor speeds). Of course this would just be for the 'learning phase' and then when it faces humans it can be placed back on it's limitation handicap (the robotics interface, APM cap, etc.) | ||
VioleTAK
Israel4279 Posts
At the beginning of the game I believe AlphaGo could at some point be so good with micro, like was suggested as an example in this thread: Muta harass, on levels that humans never faced before. In Go, AlphaGo kind of "becomes stronger" as the game progresses, which is basically saying that humans become more limited, and can come up with unthinkable moves. But in BW I believe the longer the game lasts, AlphaGo would get outshined by humans for various reasons, some of which Boxer mentioned. Question is if humans could even reach an extended game against that perfect micro. Another interesting point is that AlphaGo started to get so good at Go when it played itself, millions and millions of times. Can it really do that with Starcraft? Not to mention the various maps. Go is infinitely more complex and deep than any game including Starcraft of course, there's no comparison there, but it is an entirely different story to reach a point where it teaches itself BW on a pro+ level, I think they have quite a challenge ahead if they really intend to continue, and I hope they do. Starcraft is feels a lot more like "real" war than Go of course, and I also think that if AlphaGo would become better than top pros then... many countries will gain interest in developing A.I. for military use. It sounds ridiculous that Starcraft/AlphaGo could initiate such a thing but it's not that farfetched. Anyway, Boxer is pure <3 :-) | ||
todespolka
221 Posts
On March 13 2016 02:38 Axieoqu wrote: I would assume Starcraft would be even easier for the AI because mechanics are so important. Just consider how well the simple blink/micro bots work. It has to issue commands and receive information the same way as a human. The apm is probably also capped, because you want to know if an ai is able to do as well as a human with a limited amount of apm. It has one advantage it doesn't get tired. An automate can already beat a human in a micro battle, that is not the goal of ai research (look for sc2 automaton micro battle). It is easy to determine what a good move is in go and in chess. But starcraft has no perfect moves, you have many good moves. Another difficulty is that starcraft is a fast game. Human brain is made for fast things. An example: Human brain is able to recognize on a picture all objects at once (roughly). This is possible because neurons can work all at once. Scientists say that the brain recognizes a face in only 100 steps. Can you imagine a piece of code which does that? Our brain is nothing else than a very complex computer and one day we will be able to copy and improve it. But if that day comes we will also enhance our own brain and maybe link it with the super computer. Who knows! | ||
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Arrian
United States889 Posts
On May 26 2017 23:20 todespolka wrote: It has to issue commands and receive information the same way as a human. The apm is probably also capped, because you want to know if an ai is able to do as well as a human with a limited amount of apm. An ai can already beat a human in a micro battle if it can work directly with the game engine and if it has unlimited apm (look for sc2 automaton micro battle). If AI ends up succeeding, we can certainly anticipate all sorts of allegations and complaints about the AI cheating along those lines. | ||
Erik.TheRed
United States1655 Posts
On May 26 2017 23:20 todespolka wrote: It has to issue commands and receive information the same way as a human. The apm is probably also capped, because you want to know if an ai is able to do as well as a human with a limited amount of apm. An ai can already beat a human in a micro battle if it can work directly with the game engine and if it has unlimited apm (look for sc2 automaton micro battle). Yup, capping APM/ imposing some physical limitations will also force the AI to prioritize its 'attention' during a match. I would argue that the game of Starcraft (or any RTS) is contingent on that limitation. It will be fascinating to see how an attention-limited AI will adjust to the dynamics of a game where a big part of high-level play is trying to distract the other player. | ||
mishimaBeef
Canada2259 Posts
Also, note that whatever parameters you decide on to make it "fair", this AI will never get fatigued or make mental mistakes. Unless of course you want to include code for that sort of thing. IMO, it's not a matter of *if*, but *when*. | ||
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Arrian
United States889 Posts
On May 26 2017 23:35 Erik.TheRed wrote: Yup, capping APM/ imposing some physical limitations will also force the AI to prioritize its 'attention' during a match. I would argue that the game of Starcraft (or any RTS) is contingent on that limitation. It will be fascinating to see how an attention-limited AI will adjust to the dynamics of a game where a big part of high-level play is trying to distract the other player. That's an interesting thought. I can definitely see how the training methods of AI would help it choose some wickedly smart dropship vectors, or really clever and unexpected corsair/reaver micro, things like that. Where I see it having humongous problems is with higher level reasoning. So like today, I was watching Soulkey's stream and he was playing a ZvT where intuitively I thought to myself that there should definitely be Science Vessels out, but there were none, so there must be drops coming. I knew that, because the only thing that would delay the vessels is if dropships were being built instead of vessels. And just as I thought that, two scourge popped for Soulkey and he put them on patrol on the exposed path to his main. He was thinking the same thing. How would an AI make that determination? I'm not saying it can't, but it's a very high level inference+accompanying action. And god help it, I will admit defeat to the machines if it can figure out something like Nal_Ra's arbiter hallucination win on the first go (without detection obviously). | ||
todespolka
221 Posts
On May 26 2017 23:35 Erik.TheRed wrote: Yup, capping APM/ imposing some physical limitations will also force the AI to prioritize its 'attention' during a match. I would argue that the game of Starcraft (or any RTS) is contingent on that limitation. It will be fascinating to see how an attention-limited AI will adjust to the dynamics of a game where a big part of high-level play is trying to distract the other player. This is the interesting part. In addition to that it has also to know where to position units best and when, how to scout, understand the map, know how to take a risk and many other things. | ||
mishimaBeef
Canada2259 Posts
Not only is it playing 1000 games, it is playing them at their best ability. Progamers these days may play 40 games a day but, first they are not systematically (with machine precision) developing their skill set in relation to their strategy and mechanics, and second their opponents aren't playing at absolute top tier performance for all 40 games. The machine if playing against itself will always be testing itself against the top performing strategy and mechanics, executed at machine precision. These things considered, the rate of growth of the AI is insurmountable by humans. | ||
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Arrian
United States889 Posts
On May 26 2017 23:55 mishimaBeef wrote: If the AI is capable of playing, let's say, 1000 games against itself per day, I think you really need to think about the implications of this. Not only is it playing 1000 games, it is playing them at their best ability. Progamers these days may play 40 games a day but, first they are not systematically (with machine precision) developing their skill set in relation to their strategy and mechanics, and second their opponents aren't playing at absolute top tier performance for all 40 games. The machine if playing against itself will always be testing itself against the top performing strategy and mechanics, executed at machine precision. These things considered, the rate of growth of the AI is insurmountable by humans. I think you may be making a mistake here. If you cap AI mechanical performance to something reasonably high (350, say), then humans and AI are both approaching if not basically at the asymptotes for win% gain on the mechanical front. In other words, improving your AI's mechanics by a lot over these 1000 games per day isn't going to give you much of a gain in your AI's ability to win games. Most games among pros are not won on the basis of mechanics alone. Most of it is based on information, the inferences made from that information, and proper response. Mechanics is easy. How you approach any given situation given the information you have is hard. The point that a lot of people keep bringing up in terms of the AI's shortcomings is the strategic and situational variability. Again, 1000 games is nice, but you need to be able to form good generalizations over those games in order for them to apply in a given circumstance. If you're playing 1000 games a day for 2 years of development, I can't see how you're not overfitting. Top pros aren't approaching the game from the standpoint of a massive chunk of data. They have already extracted the meaningful generalizations about most situations. 1000 games a day isn't going to do much but give the AI improvements in the marginal areas of win% gain. I say this because "strategy" and mechanics aren't so much where the game is won. The bulk of the game is scouting and reacting. It's about knowing the right inferences to make for a relatively small amount of information. The right way to approach teaching an AI how to do that may or may not take the form of a massive chunk of data, that's an empirical question, but given the methods that will probably be used to train these AIs, tuning them to make the right inferences for an enormous space of possibilities is a huge challenge. But that's where games are won. Some are won with mechanics, sure, and some are won with strokes of brilliant strategy, but in reality, most games are won by making accurate inferences from little information and then knowing the right response and executing it. That's basically the opposite of what AI is good at. AI is good at making accurate inferences from an enormous quantity of information, especially when there's no information asymmetry. It's a much tougher task than you're making it out to be. | ||
mishimaBeef
Canada2259 Posts
In the AIs case, all the learning it does with regard to strategy is correct and not muddled by an opponent that poorly executed and made you think your strategy was sound in some way. | ||
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Arrian
United States889 Posts
On May 27 2017 00:13 mishimaBeef wrote: The reason I brought up mechanics is that you can be making false inferences about strategic elements of the game simply because your strategy or tactics happened to work against a player that wasn't executing at top mechanical level. In the AIs case, all the learning it does with regard to strategy is correct and not muddled by an opponent that poorly executed and made you think your strategy was sound in some way. I don't think there's any question that the AI will learn the ways people play and quickly. Like you'd have to show it only 100 games if not fewer of ZvT to figure out that it should having mutalisks by the 7 minute mark and they should be doing stuff. But that's not at all what's impressive. What's impressive is ee han timing. What's impressive is knowing when you had an advantage and where to press that advantage. I have a very hard time believing that Jaedong knew Stork was weak when he went for the muta timing attack because he'd seen 1000 games like it. He'd probably never seen a game like that one before. But he knew Stork was weak because he'd done some quick mental calculations and some inferences based on what he'd seen from his opponent. I'm not an expert, but I do have experience in some machine learning techniques, and that's not at all how they learn or "think." From what I understand to be the case, getting a machine to do something like that is extremely difficult and not easily solved just by throwing data at it. Machine learning people have tried throwing mountains of data at a problem before, and that technique has failed in the past. Just saying it's going to see oh-so-much-data-and-be-oh-so-smart-you-guys isn't really an accurate representation of the challenge or solution. | ||
mishimaBeef
Canada2259 Posts
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