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Sounds like you have several problems with the way your policy is parametrized. You don't have to use the multivariate normal distribution. It can work, and probably others have done it already (if not with AAC, surely with DDPG, as it'll be easier to derive the policy gradient there). I won't explain how to use the multivariate normal with either case as ...


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I am not an expert in RL. I have been playing Go for some years. Let's quote from AlphaZero's paper first: Aside from komi, the rules of Go are also invariant to colour transposition; this knowledge is exploited by representing the board from the perspective of the current player (see Neural network architecture). In the Game of Go, the difference between ...


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