I’m new to Nengo and the neuromorphic field. I want to implement a model that controls a robot with reinforcement learning in Nengo.
I’ve read a lot of stuff before I go, but I’m confused… I saw the hierarchy reinforcement learning (HRL) implementation that built the entire model of Q-Learning directly with spiking neurons.
On the other hand, I saw that you have the Nengo DL that can “convert” regular non-spiking Keras models into spiking ones.
I don’t know which way to go and what are the benefits of every choice. The easiest thing for people with experience in Keras is probably the Nengo DL. But if it was so easy to convert non-spiking models to spiking ones, no additional effort was needed for a thesis like the HRL…
Any suggestion would be highly appreciated.