Training neural networks with extension R in NetLogo

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Training neural networks with extension R in NetLogo

NetLogo-Users mailing list
Good day,
 

 I am creating a supply chain simulation with NetLogo. I am putting a list of lists from NetLogo to R, which is represented by distributor ID (agents who) and sales history (sales of all previous ticks). In R I train my neural network and make predictions. When I put back the answer in the same format list of lists. I need to specify which result goes to which agent. However, I do not know how to do it in NetLogo. I assume that there should be a function to do that, but as I understand the functions are programmed with Java and I would need to assign the values inside the raw code and not in the NetLogo environment. Moreover, I think that this training and predictions occurs multiple times (for each agent) and not only once.
 Variable example:
 [ [0] [ 100 200 300 100 200] ]
 [ [1] [ 200 300 100 100 200] ]
 Where the first index is agents who index and the second is the agent's sales history.
 Maybe someone could explain how NetLogo and R can be combined for computational purpose and not only statistical analysis and plotting? I assume that NetLogo is similar to parallel programming, while my style of R programming is more linear.