Recently I’m looking into learning mechanism in neuroscience and also Nengo,
but I’m not quite there yet, just in the exploring phase.
I’ve follow the examples about supervised learning and unsupervised learning in the newly uploaded Nengo 2.4 documetation.
If I understood those in the right way, they presented how the neural network establish the functional connection, through PES and/or BCM rules, in the lower level (neuroscience level).
But if we doesn’t need to observe the online process of the connection learning behavior, we can just utilized the connection solver provided by nengo simulator to determine the synaptic weighting of the network to have the network performs the desired transform of function.
Now I’m more interested in the cognitive level of learning behavior, since it’s more applicable to real world task solving, say let the robot learn as trial.
I noticed that there’s a example utilizes Voja rule to perform SPA level learning which is really interesting, but not seems to cover the learning behavior in general or, say reinforcement learning.
So, I would like to see more suggestion in modeling of learning behavior with Nengo.
Any discussion is welcomed!