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I mean, interacting with the mouse and keyboard isn't the interesting part. Like, imagine if this was a chess AI, and we were trying to determine who was bette

by stale2002 8y ago

I mean, interacting with the mouse and keyboard isn't the interesting part. Like, imagine if this was a chess AI, and we were trying to determine who was better at chess, humans or AI. Would you make the AI use robotic hands to move the pieces? No, because thats not the interesting part of chess. The interesting part of chess is the strategy.

RodericDay 8y ago
frame and position perfect spell casting is like an aimhack in counterstrike bots are really really good at FPSs with zero ML, just because its easy to point and click at the right position if you're fed its coordinates directly
moogly 8y ago
There is 0 mechanical skill involved in chess. Reflexes don't matter. There is mechanical skill involved in Dota 2, and reflexes matter. And consider a game like Quake where mechanical skill is even more important (even though mechanical skill matters, Dota 2 is still primarily a game about strategy and team coordination).
- shagie 8y ago
  I would encourage you to watch this APM demonstration https://www.youtube.com/watch?v=YbpCLqryN-Q https://www.youtube.com/watch?v=YbpCLqryN-Q , give https://www.engadget.com/2014/10/24/starcraft-2-and-the-quest-for-the-highest-apm/ https://www.engadget.com/2014/10/24/starcraft-2-and-the-ques... a read (600 APM) and consider how much of an advantage the computer has.
  - kolinko 8y ago
    APM matters less in Dota than in Starcraft
andrei_says_ 8y ago
Interacting with the mouse and keyboard at this speed and precision is absolutely a very interesting part for me. It is a limitation of he human organism. What if we could pit humans and ai bots at the speed of human imagination?
- stale2002 8y ago
  It could be interesting, but playing DotA just isn't the best problem to test this problem on. One could imagine a much better way of testing hand eye coordination, through a serious of mazes or puzzles or reaction tests. It would be like trying to test hand key coordination by having a robot play physical chess against a person.
king07828 8y ago
Agreed that the strategy is an interesting part. Another interesting part will be creating an AI / neural network that can utilize inputs that are closer to human level inputs (e.g., using the frame buffer and audio out as input to the neural network and passing the outputs of the neural network to a keyboard and mouse driver). Just let the network train itself without having a human laboriously determine the topology of the neural network. Such a neural network can then be applied to several different types of games / problems much more quickly than at present where significant human labor is required to generate deeply customized neural networks for each game / problem.
- rhaps0dy 8y ago
  >Just let the network train itself without having a human laboriously determine the topology of the neural network I hope this little koan illustrates that this sentence is impossible to execute. The human always has to specify something. -- In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What are you doing?", asked Minsky. "I am training a randomly wired neural net to play Tic-tac-toe", Sussman replied. "Why is the net wired randomly?", asked Minsky. "I do not want it to have any preconceptions of how to play", Sussman said. Minsky then shut his eyes. "Why do you close your eyes?" Sussman asked his teacher. "So that the room will be empty." At that moment, Sussman was enlightened.
  - king07828 8y ago
    Agreed that without any constraints, it could become a Sisyphean task. The exercise then becomes one of finding the minimal constraints needed to achieve the desired results. Please correct if needed, but looking at the Dota 2 neural network [1], it boils down to generating an input State vector from the Dota 2 bot output interface, running the state Vector through an lstm (of sufficient length) to generate an output State vector, and generating the inputs for the Dota 2 bot input interface from the output State vector. Update this network (1) to have the input State Vector generated from a convolutional network that feeds a fully connected Network and uses the frame buffer as input and (2) to have the final outputs of the neural network be keyboard and mouse commands instead of dota 2 bot input interface commands, then let the network train itself. The number of elements in the state vector, the number of convolutional layers, the number of lstm layers, and the number of layers and elements in each fully connected hidden layer could each also be determined by a recurrent neural network. [1] https://towardsdatascience.com/the-science-behind-openai-five-that-just-produced-one-of-the-greatest-breakthrough-in-the-history-b045bcdc2b69 https://towardsdatascience.com/the-science-behind-openai-fiv... (see the image under "The Architecture") [ random capitalization powered by Google speech dictation ]

RodericDay 8y ago

frame and position perfect spell casting is like an aimhack in counterstrike bots are really really good at FPSs with zero ML, just because its easy to point and click at the right position if you're fed its coordinates directly

moogly 8y ago

There is 0 mechanical skill involved in chess. Reflexes don't matter. There is mechanical skill involved in Dota 2, and reflexes matter. And consider a game like Quake where mechanical skill is even more important (even though mechanical skill matters, Dota 2 is still primarily a game about strategy and team coordination).

shagie 8y ago
I would encourage you to watch this APM demonstration https://www.youtube.com/watch?v=YbpCLqryN-Q https://www.youtube.com/watch?v=YbpCLqryN-Q , give https://www.engadget.com/2014/10/24/starcraft-2-and-the-quest-for-the-highest-apm/ https://www.engadget.com/2014/10/24/starcraft-2-and-the-ques... a read (600 APM) and consider how much of an advantage the computer has.
- kolinko 8y ago
  APM matters less in Dota than in Starcraft

andrei_says_ 8y ago

Interacting with the mouse and keyboard at this speed and precision is absolutely a very interesting part for me. It is a limitation of he human organism. What if we could pit humans and ai bots at the speed of human imagination?

stale2002 8y ago
It could be interesting, but playing DotA just isn't the best problem to test this problem on. One could imagine a much better way of testing hand eye coordination, through a serious of mazes or puzzles or reaction tests. It would be like trying to test hand key coordination by having a robot play physical chess against a person.

king07828 8y ago

Agreed that the strategy is an interesting part. Another interesting part will be creating an AI / neural network that can utilize inputs that are closer to human level inputs (e.g., using the frame buffer and audio out as input to the neural network and passing the outputs of the neural network to a keyboard and mouse driver). Just let the network train itself without having a human laboriously determine the topology of the neural network. Such a neural network can then be applied to several different types of games / problems much more quickly than at present where significant human labor is required to generate deeply customized neural networks for each game / problem.

rhaps0dy 8y ago
>Just let the network train itself without having a human laboriously determine the topology of the neural network I hope this little koan illustrates that this sentence is impossible to execute. The human always has to specify something. -- In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What are you doing?", asked Minsky. "I am training a randomly wired neural net to play Tic-tac-toe", Sussman replied. "Why is the net wired randomly?", asked Minsky. "I do not want it to have any preconceptions of how to play", Sussman said. Minsky then shut his eyes. "Why do you close your eyes?" Sussman asked his teacher. "So that the room will be empty." At that moment, Sussman was enlightened.
- king07828 8y ago
  Agreed that without any constraints, it could become a Sisyphean task. The exercise then becomes one of finding the minimal constraints needed to achieve the desired results. Please correct if needed, but looking at the Dota 2 neural network [1], it boils down to generating an input State vector from the Dota 2 bot output interface, running the state Vector through an lstm (of sufficient length) to generate an output State vector, and generating the inputs for the Dota 2 bot input interface from the output State vector. Update this network (1) to have the input State Vector generated from a convolutional network that feeds a fully connected Network and uses the frame buffer as input and (2) to have the final outputs of the neural network be keyboard and mouse commands instead of dota 2 bot input interface commands, then let the network train itself. The number of elements in the state vector, the number of convolutional layers, the number of lstm layers, and the number of layers and elements in each fully connected hidden layer could each also be determined by a recurrent neural network. [1] https://towardsdatascience.com/the-science-behind-openai-five-that-just-produced-one-of-the-greatest-breakthrough-in-the-history-b045bcdc2b69 https://towardsdatascience.com/the-science-behind-openai-fiv... (see the image under "The Architecture") [ random capitalization powered by Google speech dictation ]