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I wonder how long it will be for them to build a version that actually uses the screen images as opposed to all the data from the Bot API. Seems like it would b

I wonder how long it will be for them to build a version that actually uses the screen images as opposed to all the data from the Bot API. Seems like it would be a lot harder when you add an image processing step and restrict processing of information from across the map without actually scrolling over there.

minimaxir 8y ago
Per the architecture, the model does use a CNN to process minimap data.
- sgillen 8y ago
  Yes but the comment you're replying to is saying that it would be interesting to only rely on information from visual input on the screen, rather than on getting (for example) the absolute XY position of every player as a direct input to the network.
  - wetpaws 8y ago
    It's like writing a bot that would play chess using video feed from camera. Yes, it's doable and an interesting problem on it's own but completely unrelated to what openai is doing.
    - sgillen 8y ago
      yes I see what you are saying with the chess example, but I think in this case adding the visual layer actually adds interesting problems related to what openAI is trying to do. See my reply to lawrenceyan above.
    - adamrezich 8y ago
      Chess is a poor example because it's a turn-based game whereas Dota is real-time and incredibly fast-paced. Visually parsing a chessboard to know which piece is which is trivial, and also you have all the time in the world to do it (between turns). In Dota things happen so quickly, particle effects pop off all over the place, and through all of it, you have to constantly manually re-place your camera in the optimal position. In chess, both players always have perfect information about the game-state, and this is far from the case in Dota. OpenAI does account for fog of war, so it's not COMPLETELY omniscient, but it is still more omniscient than human players ever have the ability to be, without having to fiddle with the camera etc.
lawrenceyan 8y ago
The point isn't to see if the model can process images. OpenAI's goal is to see if they can recreate the ability to plan and strategize over a partial information continuous long time horizon environment. You wouldn't want AlphaGo to have to input it's commands using robotic hands right? It's the same thing in that, sure it might be interesting, but that isn't what we care about. Image processing and robotics controls are largely solved. Showcasing that a model can gain the ability to plan and think is the novel stuff here, and is the path to where "artificial intelligence" if any appears. That's the ultimate goal in playing any of these games.
- sgillen 8y ago
  >> Image processing and robotics controls are largely solved Image processing and robotic control are very far from being solved problems. I guess you are saying that in the case of alpha go it would not be a super difficult step to have a camera and robotic hand physically move pieces around, and that's probably true. But I think in the DOTA case are new image processing challenges that interact with the AI in interesting ways. I'm mostly talking about the need to move the game's camera around to gain more information. If you don't see your ally on your screen and need to see how they are handling a gank or something (full disclosure I don't play DOTA at all this could be a silly scenario). Then the AI would have to recognize this and move the camera to the allies location in order to gain that information. So really the novelty here would be in the network to somehow realize what information it needs and then further to learn how to gather that information. I honestly think that sounds like an extremely difficult next step.
  - nsomaru 8y ago
    This is something i noticed; a human initiator would get counter initiated almost instantly, every single time by OpenAI. The blink dagger is much less effective. Pro humans do this too, but not every single time with perfect timing. Humans dont concentrate on the whole screen, attention is directed...
    - jacoblambda 8y ago
ufo 8y ago
According to the Q&A at the end of the event, one of the main obstacles for using the regular game as output instead of the bot API is that self play would become prohibitively expensive. The AI plays thousands and thousands of games every day and you would need an enormous amount of GPU resources to render all of those.
- ambicapter 8y ago
  That's just equal footing, I say.
  - ufo 8y ago
    To be pedantic, equal footing here would be about GPU resources needed to interpret the images. The point I mentioned was about the GPU resources needed to render them to the screen in the first place.
- skgoa 8y ago
  That's a bullshit argument. You can seperate the CV portion from the analysis portion and just train the analysis portion by giving it realistcally limited information.
Karlozkiller 8y ago
I'd say the technology for building a bot with computer vision is already here or close to it. So building a working one would not take long. The problem, as they stated in the QnA is that the image processing would take much more hardware and computing power, this increasing both cost and training time, as you would not be able to run games as quickly anymore.

minimaxir 8y ago

Per the architecture, the model does use a CNN to process minimap data.

sgillen 8y ago
Yes but the comment you're replying to is saying that it would be interesting to only rely on information from visual input on the screen, rather than on getting (for example) the absolute XY position of every player as a direct input to the network.
- wetpaws 8y ago
  It's like writing a bot that would play chess using video feed from camera. Yes, it's doable and an interesting problem on it's own but completely unrelated to what openai is doing.
  - sgillen 8y ago
    yes I see what you are saying with the chess example, but I think in this case adding the visual layer actually adds interesting problems related to what openAI is trying to do. See my reply to lawrenceyan above.
  - adamrezich 8y ago
    Chess is a poor example because it's a turn-based game whereas Dota is real-time and incredibly fast-paced. Visually parsing a chessboard to know which piece is which is trivial, and also you have all the time in the world to do it (between turns). In Dota things happen so quickly, particle effects pop off all over the place, and through all of it, you have to constantly manually re-place your camera in the optimal position. In chess, both players always have perfect information about the game-state, and this is far from the case in Dota. OpenAI does account for fog of war, so it's not COMPLETELY omniscient, but it is still more omniscient than human players ever have the ability to be, without having to fiddle with the camera etc.

lawrenceyan 8y ago

The point isn't to see if the model can process images. OpenAI's goal is to see if they can recreate the ability to plan and strategize over a partial information continuous long time horizon environment. You wouldn't want AlphaGo to have to input it's commands using robotic hands right? It's the same thing in that, sure it might be interesting, but that isn't what we care about. Image processing and robotics controls are largely solved. Showcasing that a model can gain the ability to plan and think is the novel stuff here, and is the path to where "artificial intelligence" if any appears. That's the ultimate goal in playing any of these games.

sgillen 8y ago
>> Image processing and robotics controls are largely solved Image processing and robotic control are very far from being solved problems. I guess you are saying that in the case of alpha go it would not be a super difficult step to have a camera and robotic hand physically move pieces around, and that's probably true. But I think in the DOTA case are new image processing challenges that interact with the AI in interesting ways. I'm mostly talking about the need to move the game's camera around to gain more information. If you don't see your ally on your screen and need to see how they are handling a gank or something (full disclosure I don't play DOTA at all this could be a silly scenario). Then the AI would have to recognize this and move the camera to the allies location in order to gain that information. So really the novelty here would be in the network to somehow realize what information it needs and then further to learn how to gather that information. I honestly think that sounds like an extremely difficult next step.
- nsomaru 8y ago
  This is something i noticed; a human initiator would get counter initiated almost instantly, every single time by OpenAI. The blink dagger is much less effective. Pro humans do this too, but not every single time with perfect timing. Humans dont concentrate on the whole screen, attention is directed...
  - jacoblambda 8y ago

ufo 8y ago

According to the Q&A at the end of the event, one of the main obstacles for using the regular game as output instead of the bot API is that self play would become prohibitively expensive. The AI plays thousands and thousands of games every day and you would need an enormous amount of GPU resources to render all of those.

ambicapter 8y ago
That's just equal footing, I say.
- ufo 8y ago
  To be pedantic, equal footing here would be about GPU resources needed to interpret the images. The point I mentioned was about the GPU resources needed to render them to the screen in the first place.
skgoa 8y ago
That's a bullshit argument. You can seperate the CV portion from the analysis portion and just train the analysis portion by giving it realistcally limited information.

Karlozkiller 8y ago

I'd say the technology for building a bot with computer vision is already here or close to it. So building a working one would not take long. The problem, as they stated in the QnA is that the image processing would take much more hardware and computing power, this increasing both cost and training time, as you would not be able to run games as quickly anymore.