The DIAMOND Model: Deep Recurrent Neural Networks for Self-Organizing Robot Control - Smith, Simón C.; Dharmadi, Richard; Imrie, Calum; Si, Bailu; Herrmann, J. Michael (Frontiers in Neurorobotics, 2020)
The proposed architecture applies the principle of predictive coding and deep learning in a brain-inspired approach to robotic sensorimotor control. It is composed of many layers each of which is a recurrent network. The component networks can be spontaneously active due to the homeokinetic learning rule, a principle that has been studied previously for the purpose of self-organised generation of behaviour. We present robotic simulations that illustrate the function of the network and show evidence that deeper networks enable more complex exploratory behaviour.