MLP
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These networks take a single state as input. They are composed of a sequence of dense (fully connected) layers. MLPs are general purpose, simple networks. Well suited for environments with a low dimensional state space, or a state space with no spatial structure.
Refer to the class documentation and example net spec from the source:
This specification instantiates an MLP with 3 hidden layers of 256, 128, and 64 nodes respectively, rectified linear (ReLU) activations, and the optimizer with a learning rate of 0.02. The rest of the spec is annotated below.
For more concrete examples of net spec specific to algorithms, refer to the existing .