However, I don't think it's a bad next step to train AI's to play game.
Even though games lack several of the difficulties of real world tasks, playing them well is just beyond our current capabilities. It is good to successively solve hard problems, rather than wait for the perfect unified answer to everything thing.
It may, or may not be on a useful path to solving harder AI problems. I don't know. But it's a good way of demonstrating value (and publishing papers).
The article doesn't really focus on algorithms, but rather reward functions. In this case, the evolutionary algorithm has a reward function that tells it which mutations are most useful and therefore should be used to generate new mutations.
This reward function is essentially the same no matter if you do normal reinforcement learning or evolutionary.
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[ 2.8 ms ] story [ 15.6 ms ] threadHowever, I don't think it's a bad next step to train AI's to play game.
Even though games lack several of the difficulties of real world tasks, playing them well is just beyond our current capabilities. It is good to successively solve hard problems, rather than wait for the perfect unified answer to everything thing.
https://www.youtube.com/watch?v=qv6UVOQ0F44
It may, or may not be on a useful path to solving harder AI problems. I don't know. But it's a good way of demonstrating value (and publishing papers).
This reward function is essentially the same no matter if you do normal reinforcement learning or evolutionary.