Comments (3)
Hi @coreyhahn -- we do support nested observation spaces -- acme itself actually doesn't make any assumptions about the observation structures. These assumptions are captured in the networks. So, for example, if you are using the default Atari network for DQN, that assumes that the inputs are images. If you want to handle nests, you could easily define your own network as a Sonnet module; you might find tree useful for manipulating the nested data structures of arrays/tensors.
Let me know how it goes!
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I think i have a lead. I think i need to flatten the observation space because acme/tensorflow does not support tuple or dictionary observation spaces.
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It seems that this question was sufficiently answered. Closing the issue.
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