[nengo-user] Using NENGO in agent based modeling

[Panagiotis Sakagiannis]

Hello

I am trying to combine Nengo with an agent based modeling (ABM) platform.
The idea is that I want each agent to be controlled by a neural network,
which will be modifiable, adaptive and evolvable. This means that on each
time step the input that the agent senses from the environment will be
passed onto the neural network and the output will be executed as action in
the ABM. The neural network will function in continuous time and its state
will be preserved until the next time step of the ABM simulation.

Up to now I am using Repast Simphony which is written in Java. Ideally I
would like to build my neural network in Nengo and export the java code to
use it in Repast and vice versa inspect any modifications, learning or
evolution of the NN back in Nengo. Up to now I was using some NN libraries
(Simbrain) and writing the code straight in Java but it seems Nengo can be
more appropriate for my goals.

Would the aforementioned pipeline be possible? What would be the best way
to integrate Nengo to a java application, so that several continuously
running NNs can be fed with input, retrieve the output, preserve the NN
state until the next time it is called through the java code of the ABM
simulation? Also inspect the NN through the data retrieval and storing
perfomed in the simulation.

How would you implement such an integration?
Any suggestions or ideas are welcome.

Thank you for your time

Sakagiannis Panagiotis
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