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DeepMind StarCraft II Demonstration [video]

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Re: DeepMind StarCraft II Demonstration [video]

#111

Post by roenxi »

darkmighty wrote: post #87

I was left unconvinced (reproducing my comment from reddit): AlphaStar had 0 cost to sense the entire map simultaneously, and when they introduced the attention/context switching cost (camera control) in the showmatch, it lost. Also very notable for me in the showmatch was it seemed completely blind and exploitable to some strategies. When AlphaGo played top players, it made a few mistakes, but there wasn't anything…

The original AlphaGo showing (vs Fan Hui) had obvious problems. They weren't catastrophic, it was clearly playing at a professional level stronger than 1d, but it also wasn't obviously superhuman. Lee Sedol could have expected to win his matches, and not been arrogant about it.

The gap between that AlphaGo and the AlphaGo that beat Lee Sedol was probably something like 10 years of human improvement compressed into a couple of months. 500 Elo is huge.

Even if they still have further to go, comparing this to AlphaGo's progress is reasonable. I'm going to live dangerously and make an assumption - you probably understand Starcraft better than Go, so can see the flaws more easily. Any mistake in Go comes back to something the AI just didn't see.

Re: DeepMind StarCraft II Demonstration [video]

#112

Post by andreyk »

roenxi wrote: post #111
darkmighty wrote: post #87

I was left unconvinced (reproducing my comment from reddit): AlphaStar had 0 cost to sense the entire map simultaneously, and when they introduced the attention/context switching cost (camera control) in the showmatch, it lost. Also very notable for me in the showmatch was it seemed completely blind and exploitable to some strategies. When AlphaGo played top players, it made a few mistakes, but there wasn't anything…

The original AlphaGo showing (vs Fan Hui) had obvious problems. They weren't catastrophic, it was clearly playing at a professional level stronger than 1d, but it also wasn't obviously superhuman. Lee Sedol could have expected to win his matches, and not been arrogant about it. The gap between that AlphaGo and the AlphaGo that beat Lee Sedol was probably something like 10 years of human improvement compressed into a…

StarCraft is also a FAR bigger challenge than Go. So much so that even saying AlphaStar is similar to AlphaGo is quite a stretch (see https://deepmind.com/blog/alphastar-mastering-real-time-stra... - the architecture and to some extent training regime are very different). I'd be surprised if they can learn the macro without imitation, unlike in Go ; but we'll see. Would sure be nice if they also released the paper...

Re: DeepMind StarCraft II Demonstration [video]

#113

Post by YeGoblynQueenne »

darkmighty wrote: post #87

I was left unconvinced (reproducing my comment from reddit): AlphaStar had 0 cost to sense the entire map simultaneously, and when they introduced the attention/context switching cost (camera control) in the showmatch, it lost. Also very notable for me in the showmatch was it seemed completely blind and exploitable to some strategies. When AlphaGo played top players, it made a few mistakes, but there wasn't anything…

I'm always partial to a good argument for being sceptical of such announcements (I'm a professional skeptic; "researchers", some people call us), but in this case the question is whether it is ever possible to make the comparison fair at all. For example, we can restrict the AI player to perceive the game world in the same way (iiish) as the human player, but we can't really make the human player see the game world in the same way as the AI player. So if the AI player has an inherent advantage because of its superior perception, there's just no way to level the field and compare the human to the AI in a fair manner. Perhaps we just have to accept that a human will never have an advantage against a computer player in a computer game, or that computer games are just not very interesting testbeds for AI, after all (that would be very controversial).

On the other hand, it's also useful to remember that previous attempts have been made to develop strong Starcraft players, and they all had access to the same API as the DeepMind player, yet they didn't perform as well. Of course it makes a difference that it's DeepMind who achieved this and they seem to have spared no costs in hardware and training time, unavailable to a smaller team. Perhaps we shouldn't be that surprised to learn that a poweful computer can do better than a human in some cases. But, at the end of the day, the result they got against MaNa shows that it is possible for an AI player to beat a strong human player -fairly or unfairly- in a game that was rightly considered very hard for AI players, under any assumption.

Re: DeepMind StarCraft II Demonstration [video]

#114

Post by WhompingWindows »

cjbprime wrote: post #58
Veelox wrote: post #50

Earlier quoted context omitted.

According to a site [1] Mana is 19th. While that is probably overly high, I would say he is easily in the top 200 Starcraft 2 players in the world. I would also say that to get from beating a top 200 human to beating all humans is much smaller than from scratch to beating a top 200 human. [1] https://www.gosugamers.net/starcraft2/rankings

Aligulac's had Mana around 50th in the world consistently for a recent 12 month period, so I think that's a more reasonable claim, and I'm happy saying that the 50th best player is a "top player in the world".

Aligulac is not that good, the current top 10 is highly debatable, I'd argue the only thing the current top 10 gets correct is Maru/Serral top 2, though Maru being first is a stretch as he hasn't beaten Serral and was easily countered at Blizzcon by simple strategies. I'd agree with him as #1 if he had any flexibility to not just cheese his opponents out (see Keen Ro16 matches, sOs, numerous proxies vs TY, etc.) Maru's a fantastic player but Aligulac has no way to judge his strategic inflexibility.

Re: DeepMind StarCraft II Demonstration [video]

#115

Post by darkmighty »

roenxi wrote: post #111
darkmighty wrote: post #87

I was left unconvinced (reproducing my comment from reddit): AlphaStar had 0 cost to sense the entire map simultaneously, and when they introduced the attention/context switching cost (camera control) in the showmatch, it lost. Also very notable for me in the showmatch was it seemed completely blind and exploitable to some strategies. When AlphaGo played top players, it made a few mistakes, but there wasn't anything…

The original AlphaGo showing (vs Fan Hui) had obvious problems. They weren't catastrophic, it was clearly playing at a professional level stronger than 1d, but it also wasn't obviously superhuman. Lee Sedol could have expected to win his matches, and not been arrogant about it. The gap between that AlphaGo and the AlphaGo that beat Lee Sedol was probably something like 10 years of human improvement compressed into a…

Yea stepping back a little I agree it's a fundamental achievement. It's all about expectations -- I were expecting a Lee Sedol kind of event, and it was more of a Fan Hui (or a bit further) kind of demonstration. A milestone for sure considering how difficult the problem is with various previously unconquered subchallenges (uncertainty, partial observability, massive control space), different but in some ways more difficult than OpenAI's Dota 2 matches.

> I'm going to live dangerously and make an assumption - you probably understand Starcraft better than Go, so can see the flaws more easily

Correct :) Although I'm not great at either.

This comes closer to opening doors to real uncharted territory in robotics and general agency; it trained in crazy low wall-clock time. But now we're this far it makes me question even more the cost, flexibility, adaptability, of the AI less forgivingly. How much did it actually cost to train? Would it be economical to train one of those for every single task? (e.g. in a factory or warehouse setting), Would it be vulnerable to those exploitable strategic weakness in a real world setting?, etc.

It's definitely not over yet as far as SC2 goes though :)

Re: DeepMind StarCraft II Demonstration [video]

#116

Post by kilburn »

YeGoblynQueenne wrote: post #113
darkmighty wrote: post #87

I was left unconvinced (reproducing my comment from reddit): AlphaStar had 0 cost to sense the entire map simultaneously, and when they introduced the attention/context switching cost (camera control) in the showmatch, it lost. Also very notable for me in the showmatch was it seemed completely blind and exploitable to some strategies. When AlphaGo played top players, it made a few mistakes, but there wasn't anything…

I'm always partial to a good argument for being sceptical of such announcements (I'm a professional skeptic; "researchers", some people call us), but in this case the question is whether it is ever possible to make the comparison fair at all. For example, we can restrict the AI player to perceive the game world in the same way (iiish) as the human player, but we can't really make the human player see the game world i…

A fair comparison is simple: make the AI play the game using a standard screen, mouse and keyboard (the game was designed to be played this way after all, and non-standard peripherals are not allowed in tournaments by the way). It suddenly seems WAY more challenging for the machine, doesn't it? You could also invent some contraption that interfaces directly with the human's brain to even out on the other front, but this sounds even more futuristic.

The average APM limitation is just a publicity stunt. There are similar caps one could apply that would make the challenge much more "fairer". For instance: Max (instead of average) APM or limiting mouse travel distances (no one can get even remotely close to clicking 300 times/minute on alternate sides of the screen with pixel-perfect accuracy AND timing).

Finally, the AI only plays 1 of 6 possible match-ups in 1 of infinity possible maps, and the live game has shown severe strategic mistakes (mainly the indecision when getting harassed and the inability to build a phoenix to counter the prism / keep harassing itself with the oracles instead of stupidly watching over the prism with them). It still has a long way to go for me to consider it "superior" to humans regarding intelligence (not just superhuman control).

All in all, this is still an impressive achievement though!

Re: DeepMind StarCraft II Demonstration [video]

#117

Post by dragontamer »

dllu wrote: post #77
samfriedman wrote: post #49

Earlier quoted context omitted.

As the commentators mentioned, it's no use building units to counter your enemy's army (Immortals over Stalkers) when the enemy can control their army so much more effectively. I have to wonder if future competitive games will need to take into account the abilities of reinforcement learning algorithms when releasing balance patches.

But there IS use building units to counter your enemy's army. In the last live match when Mana won, his immortal archon zealot composition was what sealed the deal in the end.

I mean, the AI in that last match couldn't see the whole map at once.

Fog of War was enabled in all cases, but the last match was them enabling the "Scrolling window" that humans are forced to look at the game with.

The AI in all of the other games could see and control all of its own units on the map simultaneously. No human has this ability due to the limitation of the screen.

Re: DeepMind StarCraft II Demonstration [video]

#118

Post by maerF0x0 »

degenerate wrote: post #56
maerF0x0 wrote: post #32

Some of the commentary shows that the UI is a barrier . The fact we can understand the strategies, but cannot physically make it happen shows that at least some of the advantage is just the precision of the inputs. Could be a new way to play SC2 like games where we can better communicate our intentions to the game. For example, make a type of move action where the stalkers automatically retreat and stop to fire, inst…

This thought process (of the UI limiting the player) is a valid point when we are talking about Human vs. AI strength and weaknesses in RTS games. However, when pitting one human player against another, the UI limitation actually adds strategic depth to the game. Unlike pure strategy games like chess, in Starcraft when you have to move, attack, move, attack, it puts a physical burden on the player. This physical burd…

I agree there are pros and cons to the physical mechanic. For example misclicks become a part of the game, whereas the RNG would be fair to each player about errors in preprogrammed walk/attack patterns.

Re: DeepMind StarCraft II Demonstration [video]

#119

Post by Dylan16807 »

orbifold wrote: post #106
Dylan16807 wrote: post #78

Earlier quoted context omitted.

It had a variety of strategies, not always making a lot of stalkers. And humans can do some really impressive blink micro too up to a certain number of units. So that's one aspect of it but isn't the main strength.

Those were not one and the same agent. If you look at the figure they released on their website the given agent would probably always have gone for a lot of blink stalkers.

We're talking about the whole package of the AI, what the entire system is capable of, so that technical detail doesn't affect kmnc's point or mine.

The biggest effect is that it's harder to change strategy midgame, which is not all that critical.

Re: DeepMind StarCraft II Demonstration [video]

#120

Post by Dylan16807 »

dragontamer wrote: post #117
dllu wrote: post #77

Earlier quoted context omitted.

But there IS use building units to counter your enemy's army. In the last live match when Mana won, his immortal archon zealot composition was what sealed the deal in the end.

I mean, the AI in that last match couldn't see the whole map at once. Fog of War was enabled in all cases, but the last match was them enabling the "Scrolling window" that humans are forced to look at the game with. The AI in all of the other games could see and control all of its own units on the map simultaneously. No human has this ability due to the limitation of the screen.

But they did say that the way the AI focused was roughly equivalent to moving the screen every couple seconds, not very different from pros, and that adding the limit didn't affect its performance against the old version.
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