5 ms·

I completely disagree. An API is software's natural input mechanism just like the senses are a human's natural input mechanism. Having the AI use human senses u

I completely disagree. An API is software's natural input mechanism just like the senses are a human's natural input mechanism. Having the AI use human senses unfairly handicaps it. More importantly, however, is that this is not the key problem. The key problem is teaching the AI strategy and tactics. What heroes to pick? Where to lane them? When to rotate? What items to buy? What spells to level up? What enemies to target with which spells and in which order? These are the hard problems and they are very hard indeed. A 5v5 AI will have to become expert at risk calculation, Pareto optimization, basic military principles, and many more things. Compared to these problems, the choice of input mechanism is trivial.

lvoudour 9y ago
>Compared to these problems, the choice of input mechanism is trivial I don't know why you think the visual/aural problem is trivial. The biggest achievement of AIs so far in this field is classification of static images
- bingojess 9y ago
  Trivial may not be the best word but what they were trying to get the AI to do was learn dota strategy and tactics. It's like teaching alphaGo to play go with a camera.
  - mirceal 9y ago
    I disagree. The representation of state is hard for machines. Go/Chess are very simple state wise when compared to Dota. By giving it API access you have eliminated guesswork/approximations from the overall picture
- BaronSamedi 9y ago
  I apologize if my statement was misleading. I do not think the visual problem itself is trivial. I think the choice of input mechanism is tangential to the hard problems actually faced by the AI designers: strategy and tactics.
_dps 9y ago
I'm almost entirely ignorant of DOTA 2, but the coverage suggests to me that it is winning mainly through what I would call "micro" excellence (firing at just the right range, careful maneuvering, and so on). It's clear that this kind of precision control is extremely advantaged by having direct access to the state of the game, rather than having to estimate it in real-time from vision data. So, to me, based purely on the news coverage, it's not clear that it has learned anything like "superhuman" levels of strategy. We already know that computers have superhuman reaction times and precision calculation abilities, so it seems to me the interesting question is whether an advantage would remain after factoring those out.
- doikor 9y ago
  > it is winning mainly through what I would call "micro" excellence This is partly it. From the interviews with the pros it mostly close to perfect micro, calculating results very well (it knows when it will win the 3 raze spam + 2 autoattacks with 2hp left and thus wins the match etc. for a human that would be hard to calculate) and due to those two it punishes every small mistake the human player makes very hard. From the actual thinking parts it had to learn creep control (pushing too far just gives free exp/last hits to the other player etc.) and itemization (what counters what, when to get ward etc.)
  - deleted 9y ago
    [deleted]
- hobofan 9y ago
  I agree. I don't think there was anything too novel in there, but it is a necessary foundation they need before advancing on to the strategy part, or they would just be out-microed there. I think there a little bit of strategy already in there since it learned about positioning, and not exposing itself too much (which is of course easier without fog of war). The only thing I was excited to see was the creep blocking, but the chance that this would turn out to be hand-trained was pretty high.
- skgoa 9y ago
  As someone who plays dota, this bot really isn't that impressive. The hero they chose is seen as a very difficult one to master for humans, precisely because judging distances, current life, current mana, damage etc. is so difficult to do on the fly and even if you can keep track of all of that in your head, you need extremely precise inputs to outplay your opponent. Yet by going through the API, they handed all of that to their bot on a silver platter. They pretty much let the bot sidestep the core challenge of this hero, while it was kept in place for the human players. On top of that they also reduced the complexity of the game quite significantly by limiting items etc., which further reduced what humans could do against the bot. Even then, the bot utterly failed once humans were allowed to use a tiny bit of creativity. And that's not even taking into account that this was not even close to the complexity of a real dota match. The big challenge in dota is in the decision making with incomplete information and in coordinating 5 people with only voice and the ability to ping the mini map, in a giant "search space" created by hundreds of different heroes, items and game mechanic interactions.
deleted 9y ago
[deleted]
marricks 9y ago
I use to think that before I read about embodied cognition [1]. I think a lot of the harder and real challenges come from acting as an agent in an environment with often fuzy information. Not only do challenges come in the form of input mechanism but potentially many rewards as well in terms of how humans process and off-load information. While I don't think DotA would be the most important example, I think having a more realistic interface is a good step. [1] https://en.m.wikipedia.org/wiki/Embodied_cognition https://en.m.wikipedia.org/wiki/Embodied_cognition artificial intelligence section probably most relevant
gerardnll 9y ago
Real life doesn't have APIs that's why AI applied to robots and cars and whatever have to be able to interpret inputs like humans.
velobro 9y ago
The Dota 2 bot is no different than Aimbots in FPS games. The bot was able to access the api to perfectly target the exact location and instantly cast a spell, much like an Aimbot can instantly get headshots.
- graphitezepp 9y ago
  It's a good comparison honestly. They stripped away all the complexity of dota to this one single scenario were the things bot's are naturally going to be good at (last hitting, precise distance evaluation) matter over strategy.
rasz 9y ago
>What items to buy? hardcoded by a pro dota 2 player hired as a consultant
- ManlyBread 9y ago
  The items are often bought depending on multitude of factors, there's no one "cookie cutter" build. On top of that the AI should be able to find more optimized buying strategies on it's own.

lvoudour 9y ago

>Compared to these problems, the choice of input mechanism is trivial I don't know why you think the visual/aural problem is trivial. The biggest achievement of AIs so far in this field is classification of static images

bingojess 9y ago
Trivial may not be the best word but what they were trying to get the AI to do was learn dota strategy and tactics. It's like teaching alphaGo to play go with a camera.
- mirceal 9y ago
  I disagree. The representation of state is hard for machines. Go/Chess are very simple state wise when compared to Dota. By giving it API access you have eliminated guesswork/approximations from the overall picture
BaronSamedi 9y ago
I apologize if my statement was misleading. I do not think the visual problem itself is trivial. I think the choice of input mechanism is tangential to the hard problems actually faced by the AI designers: strategy and tactics.

_dps 9y ago

I'm almost entirely ignorant of DOTA 2, but the coverage suggests to me that it is winning mainly through what I would call "micro" excellence (firing at just the right range, careful maneuvering, and so on). It's clear that this kind of precision control is extremely advantaged by having direct access to the state of the game, rather than having to estimate it in real-time from vision data. So, to me, based purely on the news coverage, it's not clear that it has learned anything like "superhuman" levels of strategy. We already know that computers have superhuman reaction times and precision calculation abilities, so it seems to me the interesting question is whether an advantage would remain after factoring those out.

doikor 9y ago
> it is winning mainly through what I would call "micro" excellence This is partly it. From the interviews with the pros it mostly close to perfect micro, calculating results very well (it knows when it will win the 3 raze spam + 2 autoattacks with 2hp left and thus wins the match etc. for a human that would be hard to calculate) and due to those two it punishes every small mistake the human player makes very hard. From the actual thinking parts it had to learn creep control (pushing too far just gives free exp/last hits to the other player etc.) and itemization (what counters what, when to get ward etc.)
- deleted 9y ago
  [deleted]
hobofan 9y ago
I agree. I don't think there was anything too novel in there, but it is a necessary foundation they need before advancing on to the strategy part, or they would just be out-microed there. I think there a little bit of strategy already in there since it learned about positioning, and not exposing itself too much (which is of course easier without fog of war). The only thing I was excited to see was the creep blocking, but the chance that this would turn out to be hand-trained was pretty high.
skgoa 9y ago
As someone who plays dota, this bot really isn't that impressive. The hero they chose is seen as a very difficult one to master for humans, precisely because judging distances, current life, current mana, damage etc. is so difficult to do on the fly and even if you can keep track of all of that in your head, you need extremely precise inputs to outplay your opponent. Yet by going through the API, they handed all of that to their bot on a silver platter. They pretty much let the bot sidestep the core challenge of this hero, while it was kept in place for the human players. On top of that they also reduced the complexity of the game quite significantly by limiting items etc., which further reduced what humans could do against the bot. Even then, the bot utterly failed once humans were allowed to use a tiny bit of creativity. And that's not even taking into account that this was not even close to the complexity of a real dota match. The big challenge in dota is in the decision making with incomplete information and in coordinating 5 people with only voice and the ability to ping the mini map, in a giant "search space" created by hundreds of different heroes, items and game mechanic interactions.

deleted 9y ago

[deleted]

marricks 9y ago

I use to think that before I read about embodied cognition [1]. I think a lot of the harder and real challenges come from acting as an agent in an environment with often fuzy information. Not only do challenges come in the form of input mechanism but potentially many rewards as well in terms of how humans process and off-load information. While I don't think DotA would be the most important example, I think having a more realistic interface is a good step. [1] https://en.m.wikipedia.org/wiki/Embodied_cognition https://en.m.wikipedia.org/wiki/Embodied_cognition artificial intelligence section probably most relevant

gerardnll 9y ago

Real life doesn't have APIs that's why AI applied to robots and cars and whatever have to be able to interpret inputs like humans.

velobro 9y ago

The Dota 2 bot is no different than Aimbots in FPS games. The bot was able to access the api to perfectly target the exact location and instantly cast a spell, much like an Aimbot can instantly get headshots.

graphitezepp 9y ago
It's a good comparison honestly. They stripped away all the complexity of dota to this one single scenario were the things bot's are naturally going to be good at (last hitting, precise distance evaluation) matter over strategy.

rasz 9y ago

>What items to buy? hardcoded by a pro dota 2 player hired as a consultant

ManlyBread 9y ago
The items are often bought depending on multitude of factors, there's no one "cookie cutter" build. On top of that the AI should be able to find more optimized buying strategies on it's own.