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You don't need to manage negative rewards separately, if you implemented the algorithm correctly it will work regardless if the rewards are negative or not. You seem to be using rewards for the loss but you should be using the return which is the sum of the rewards for some state action pair from that point until the end of trajectory. You also seem to be ...


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First and foremost, I have to say that this could (and likely will) be a very hard task. Neural networks (NNs) have excelled at computer vision tasks identifying everything from textures to complex objects but what you are trying to do goes beyond that. We (humans) identify trash using the context as much as the object. An object on a table and the same ...


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