Topic: fully connected multi-layer perceptrons

Artifical neural network (ANN) approaches to motor control commonly adopt generic architectures like fully connected multi-layer perceptrons (MLPs) and recurrent neural networks (RNNs). As such architectures contain few inductive biases, it is common to require priors in the form of rewards, training curricula, imitation data, or trajectory generators. In nature, animals are born with priors in the form of their nervous system's architecture, which has been shaped by evolution to confer innate ability and efficient learning. For instance, a horse can walk within hours of birth and quickly impr