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Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

arxiv.org

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Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#3
Note: it doesn't learn from pixels but features directly from RAM; and superhuman reaction time, with performance badly degrading when human-like delays added.

Good discussions on Reddit: https://www.reddit.com/r/MachineLearning/comments/5vh4ae/r_a... https://www.reddit.com/r/smashbros/comments/5vin8x/beating_t...

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#4
post #3

Note: it doesn't learn from pixels but features directly from RAM; and superhuman reaction time, with performance badly degrading when human-like delays added. Good discussions on Reddit: https://www.reddit.com/r/MachineLearning/comments/5vh4ae/r_a... https://www.reddit.com/r/smashbros/comments/5vin8x/beating_t...

we instead use features read from the game’s memory on each frame, consisting of each player’s position, velocity, and action state, along with several other values

So it's cheating, presumably knowing the opponents action before the animation even starts to play.

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#5
post #3

Note: it doesn't learn from pixels but features directly from RAM; and superhuman reaction time, with performance badly degrading when human-like delays added. Good discussions on Reddit: https://www.reddit.com/r/MachineLearning/comments/5vh4ae/r_a... https://www.reddit.com/r/smashbros/comments/5vin8x/beating_t...

I was similarly disappointed when I read this, but upon further reflection I still like this paper. It is very plausible that both of these problems could be fixed, it would just take a lot more time/power to train, and the resulting system would likely not run in real time making it impossible to test against real humans.

Further advancement in this area will require huge leaps in hardware performance. Luckily in the next few years I expect that the pace of improvement in specialized hardware for neural nets will far outpace Moore's Law.

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#6
post #3

Note: it doesn't learn from pixels but features directly from RAM; and superhuman reaction time, with performance badly degrading when human-like delays added. Good discussions on Reddit: https://www.reddit.com/r/MachineLearning/comments/5vh4ae/r_a... https://www.reddit.com/r/smashbros/comments/5vin8x/beating_t...

This reminds me of Starcraft AI experiments. They can't actually make the computer smart, so they just jam 2000 button presses per second down the tube, giving every single unit its own simultaneous AI, and it out micromanages anyone.

With Marines usually.

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#7
post #3

Note: it doesn't learn from pixels but features directly from RAM; and superhuman reaction time, with performance badly degrading when human-like delays added. Good discussions on Reddit: https://www.reddit.com/r/MachineLearning/comments/5vh4ae/r_a... https://www.reddit.com/r/smashbros/comments/5vin8x/beating_t...

we instead use features read from the game’s memory on each frame, consisting of each player’s position, velocity, and action state, along with several other values So it's cheating, presumably knowing the opponents action before the animation even starts to play.

Part of the skill in competitive play is to be able to predict what move your opponent is going to do next.

Most mid-level players already have a good grasp of prediction, which is arguably along the sames lines of being able to know with certainty what action your opponent is taking a few frames before he does it.

Coupling that with pretty obscene frame-lag for Smash, it's not really that much of an advantage.

As well that competitive isn't really that impressive considering how limited your actions are by banning items and more dynamic stages (see: restricting RNG). In this way, it's nothing more than a simple chess-bot. Now, if it could actually take in complex environments and multiple tools, that'd be pretty next level.

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#9
I think the key is limiting the reaction-time to best-human standards. If you have frame-perfect reaction time, then there's really no point in playing an AI. It should be limited to the capabilities (physically) of a human.

It's about boiling it down to strategy. With chess, you don't have to beat Deep Blue in 5 minutes. You are given ample time; analogously, one shouldn't play a computer with frame-perfect reactions but rather one that is comparable APM of a top-ten player.

Re: Beating the World’s Best at Super Smash Bros. with Deep Reinforcement Learning

#10
While the AI might be cheating by taking salient features from RAM rather than from pixel values, this is still an incredible feat. Just a few years ago we did not have generic algorithms that could take even salient features and self-learn policies to near this level this quickly.
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