Deep reinforcement learning is a waste of time (2019)

Re:Deep reinforcement learning is a waste of time (2019) by rich_sasha on Saturday July 10, 2021 @03:09PM (#27795683)

AlphaZero is not supervised, in the sense that it learned from known correct actions (earlier versions of AlphGo did learn from online games). So although it needed human supervision, sure, it didn’t need us to provide correct answers.

The authors point does somewhat stand that you don’t have the problem of reward engineering in board games so they are a dead end from that point of view - they skirt around the core problem instead of tackling it.

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Re:Deep reinforcement learning is a waste of time (2019) by freeone3000 on Sunday July 11, 2021 @12:22AM (#27798452)

AlphaZero only works on video games. If you remove its ability to judge progress by game score, which is a reward function (though not the one used, due to delayed reward issues), then it's not capable of finding its feedback. It only works in constructed environments where the environment provides the reward function implicitly. Maybe we can video-game-ify laundry folding sufficiently? I'm doubtful.

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