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I think AlphaGo vs AlphaZero is a strong argument against this. AlphaGo used the best knowledge of humanity to try to tune its play and mix human expertise, and
by TangoTrotFox 8y ago
I think AlphaGo vs AlphaZero is a strong argument against this. AlphaGo used the best knowledge of humanity to try to tune its play and mix human expertise, and centuries of master level play, with the strength of deep learning systems. It seems like this would be ideal, particularly as per your analogy. Google certainly believed this as this is the system they directed their resources towards developing and then very publicly demonstrating.
AlphaZero was likely a curious aside at one point. The idea with AlphaZero is to throw everything out the window. Even the game itself is just generalized into a generic position->transition->terminal state system where most 'simple' (in terms of rules) games can be relatively easy replaced. There was no human heuristics, no human games to go from instead relying entirely on self training, and so on. Of course it ended up that AlphaZero became vastly stronger vastly faster than AlphaGo ever managed to.
- ctchocula 8y agoIt was shocking to me too that adding prior of human games limited the potential that the go playing computer could have.
- ashelmire 8y agoHumans are so bad that fitting the network to our games trapped it in a region of local minima that weren't even close to the ideal, I guess.
- vl 8y agoAlphaZero heavily used architecture developed for AlphaGo, an in this sense there is some prior embedded in the architecture, but to jump-start development of this fine-tuned architecture human prior was useful. I.e. path from nothing to AlphaZero would be more difficult then nothing->AlphaGo->AlphaZero, imho.