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Cuce
Turkey1127 Posts
Go and chess are games of complete information, where as starcraft is a game of incomplete information. furthermore, the more information you get usually means the mroe resouce you spent on getting information. sure, a computer can calculate possible situations with given incomplete information, but to match what we call meta game and intuition of pro players, will take a really long time of self learning ana data collecting on computers part. | ||
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NinjaToss
Austria1383 Posts
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Cuce
Turkey1127 Posts
On March 11 2016 02:11 eScaper-tsunami wrote: The sad thing is it doesn't take 600 apm to have perfect micro. In the end it boils down to accuracy and efficiency. btw does broodwar has a hardlimit for command accepted per frame? like 12 per frame or something. I wouldnt be suprised if there was, at least a limit to buffering | ||
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Taf the Ghost
United States11751 Posts
On March 11 2016 02:20 Clonester wrote: But thats the point. Deepthought is not like Deep Blue brute forcing its way into the game. It is making a much more soft approach by learning to play it. The neural network architecture is not ment to brute force the game and "solve it". It learns the game by millions of games against itself and replays and learns from that, takes conclusions. Deep Blue just tried out millions of next moves when playing chess. Deep Thought learned to play the game and knows what to do where. "not like Deep Blue brute forcing its way into the game" vs "It learns the game by millions of games against itself and replays and learns from that". I don't think you quite know what "brute force" means.  I'm only poking you a little. The technology and approach are rather different between the computer systems, but they both still work by being able to call up almost the entire Game State possibility and knowing how to process through the information. This is what computers are supremely good at, but they it also shows their limitations. Though I'd be remiss if I didn't point out that most of these public games with top pro's always benefits the Computer in one very specific manner: they can analyze all of the publicly known games of the Master, allowing adaptation to the Master's play style. | ||
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L_Master
United States8017 Posts
Some form of APM cap seems fair in my book, or else the AI isn't winning because it is making better decisions than the human, it's winning because it's exploiting micro in a way no human could ever imagine. | ||
Nakajin
Canada8989 Posts
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boxerfred
Germany8360 Posts
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Savant
United States379 Posts
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Haukinger
Germany131 Posts
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disciple
9070 Posts
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Grumbels
Netherlands7031 Posts
I think neural networks are used by the planetary annihilation ai designer, I used to read some of his explanations for why that was the future of rts ai, but I don't know if he is still working on similar things or where one can find information on this. iirc the ai could learn how to micro by playing against itself over and over | ||
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endy
Switzerland8970 Posts
On March 10 2016 23:35 B-royal wrote: What will be the most difficult in my opinion is to have the AI make decisions such as where to attack, when to attack, multi-pronged attacks, when to get certain units and how to use spells such as dark swarm properly. It seems to me like it would be fairly easy to trick and abuse the behavior of the AI. I've already played a bot on BW and engagements were actually the bot's biggest strength. It's constantly scouting with zerglings, has an incredible overlord spread for a perfect map awareness which allows to always perfectly surround your army or set the best possible concave possible. As for stuffs like swarms, how many times did your defilers die before casting the swarm because you weren't selecting/clicking fast enough? | ||
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The_Red_Viper
19533 Posts
It's much more interesting in GO because there is no difference in execution, tactics and strategy is all that matters here. Even though there are a lot more possible "board states" in sc2, i am not sure if that really matters in the end if you theoretically have a player with unlimited APM and attention. But hey, i have obviously very little idea about it and when google says starcraft would be the next step, maybe it's harder than i think (or they really want to somewhat limit the AI in the mechanics department so it comes down to tactis/strategy, which would be weird though) | ||
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Goolpsy
Denmark301 Posts
There is a continuous evolution and progression of chess engines, the best one currently being 'Komodo'. From the Wiki: "Komodo heavily relies on evaluation rather than depth". I've been following the TCEC tournaments and heard the developers talk about certain aspects of the making of AI. Evaluation is derived not from knowing that a certain position withs 58% of the games, but by piece value and pieceplacement + structures. If you have a chain of pawns (x= pawn, o = empty space) oxo or oox or oxo xoo xxo xox They do not have a evaluation of 3 (1 per pawn), but more than 3. In the same way, having an isolated pawn (A pawn with no friendly pawns on either adjecent diagonal), it is usually very weak and worth less than 1. Why is this important ? Being able to evaluate a situation through dividing out the area/map is almost directly transferable to Starcraft. It can be used for unitplacement to scout, defending chokepoints, building placement or engagement angles (without too much processing even). As for incomplete information; it is not all that hard. you don't need to know all units produced to calculate possible strategies available or techtrees possible at a current time. I know it seems like it, but you don't have complete information in either chess or Go. (not that is it not a game of complete information, as you can't hold all possible iterations and payoff thereof in memory, ) | ||
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Empirimancer
Canada1024 Posts
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ZAiNs
United Kingdom6525 Posts
On March 11 2016 03:44 The_Red_Viper wrote: See the problem i have with this is that the Ai will have such a big advantage through 'mechanics' alone. It's much more interesting in GO because there is no difference in execution, tactics and strategy is all that matters here. Even though there are a lot more possible "board states" in sc2, i am not sure if that really matters in the end if you theoretically have a player with unlimited APM and attention. But hey, i have obviously very little idea about it and when google says starcraft would be the next step, maybe it's harder than i think (or they really want to somewhat limit the AI in the mechanics department so it comes down to tactis/strategy, which would be weird though) How would it be weird to limit the mechanics? The goal is to be 'smarter' than a human, without limiting mechanics it wouldn't really prove anything or be an accomplishment. I imagine they would want to even limit the mechanics so that they're slightly below the absolute best players mechanically. Attention is a resource in SC2 and I think it'll be hard to give the AI imperfect mini-map awareness or imperfect mouse-accuracy without creating too complicated of a model, but things like actual keypresses a second and cursor speed will be easy to limit. | ||
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Blargh
United States2103 Posts
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Green_25
Great Britain696 Posts
Even the micro I'm doubtful could be perfect. I may well be wrong however, and if I am this thing scares the shit out of me | ||
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Loccstana
United States833 Posts
https://webdocs.cs.ualberta.ca/~cdavid/pdf/starcraft_survey.pdf A conservative lower bound on the state space of brood war is 10^1685. This is many orders of magnitude above the state space of Go, which is 10^170. Whats more, the branching factor is 10^50 to 10^200, compared to <360 for Go. | ||
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Loccstana
United States833 Posts
On March 11 2016 02:30 Cuce wrote: Flash hit the key point I think. Go and chess are games of complete information, where as starcraft is a game of incomplete information. furthermore, the more information you get usually means the mroe resouce you spent on getting information. sure, a computer can calculate possible situations with given incomplete information, but to match what we call meta game and intuition of pro players, will take a really long time of self learning ana data collecting on computers part. Starcraft is what we call a POMDP (partially observable markov decision process), there are algorithms for solving these types of problems, for example recurrent neural networks, but no one has tried applied it to something as complex as a full game in Starcraft. | ||
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