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we already know that deep RL is sample inefficient... is meta-RL really useful for something not trivial? This seems rather silly.
by ReDeiPirati 8y ago
we already know that deep RL is sample inefficient... is meta-RL really useful for something not trivial? This seems rather silly.
- mtrazzi 8y agoThe first applications appear really simple because they illustrate cognitive abilities that imitate planning/model-based RL related to neuroscience/psychology. It doesn't mean that meta-RL won't scale up with more computation (see http://www.incompleteideas.net/IncIdeas/BitterLesson.html http://www.incompleteideas.net/IncIdeas/BitterLesson.html).