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I see that the demos in the Lab are all single_observation_space, but my experiment is multiple observation_space. Combine images and vectors into a multi-input observation space. I want to understand how to develop it. Can anyone help me? Also, I find it difficult to understand the meaning of num_states and there is no relevant explanation.
The following is the approach I found for Stable Baselines3:
Stable Baselines3 supports handling of multiple inputs by using Dict Gym space. This can be done using MultiInputPolicy, which by default uses the CombinedExtractor features extractor to turn multiple
inputs into a single vector, handled by the net_arch network.
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I see that the demos in the Lab are all single_observation_space, but my experiment is multiple observation_space. Combine images and vectors into a multi-input observation space. I want to understand how to develop it. Can anyone help me? Also, I find it difficult to understand the meaning of num_states and there is no relevant explanation.
The following is the approach I found for Stable Baselines3:
Stable Baselines3 supports handling of multiple inputs by using
Dict
Gym space. This can be done usingMultiInputPolicy
, which by default uses theCombinedExtractor
features extractor to turn multipleinputs into a single vector, handled by the
net_arch
network.Beta Was this translation helpful? Give feedback.
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