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I think the distinction is that the algorithm gets to observe the 2D space directly, whereas the whole notion of 3D space has to be learned from 2D projections.
by simonbyrne 12y ago
I think the distinction is that the algorithm gets to observe the 2D space directly, whereas the whole notion of 3D space has to be learned from 2D projections.
Also, note that the games they do best on have a nice clear objective function: Montezuma's Revenge on the other hand does not have such a numeric objective to optimise.
To be fair, Hassabis does freely concede these limitations in his talks (at least in the ones targeted to academic audiences), and it will be certainly interesting to see where they go from here.
- woodchuck64 12y ago> the whole notion of 3D space has to be learned from 2D projections. That might be extremely difficult, but nature does it with binocular vision so I would think dual vision inputs are the best way to do 3D space learning.
- deleted 12y ago[deleted]
- nemo44x 12y agoThat's a good point about Montezuma's Revenge, and similar games. Very rarely does a greedy algorithm help you in that game unlike in a breakout style game where you simply want to acquire as many points as quickly as possible.