Pedro, This is well expressed and I find it very interesting. Can you suggest a reference for your point about noise behavior in a closed loop?
You present a situation in which a cortical algorithm ought to adapt in some way. But the algorithm you describe is not an elementary loop, and I would like to give the implications more thought. Ralph On Tuesday, August 27, 2013, Pedro Tabacof wrote: > Hello, > > I've used the old NuPic for spatial classification (achieving almost the > same error rate as a SVM classifier) and read the whitepaper on the CLA, > but I haven't used the current implementation or been up to date on recent > developments. > > I was reading the thread about the Ski game and started to think if it > would be possible to apply NuPIC for MPC (Model Predictive Control), a > mature and popular technology for advanced process control. The main > difficult associated with MPC is having a reliable model of the system to > be controlled, so if a smart online learner such as NuPIC could be used to > model the system dynamics, it would be an interesting opportunity for > academic or even commercial research. > > MPC is an optimization problem where the controlled inputs are chosen to > minimize some cost function subject to the system dynamics and restrictions > for a given time horizon. After the control inputs are chosen for the whole > time window, only the next input is actually applied to the real system, > the model is updated with the system response to the chosen input, and the > optimization is done all over again. This picture sums it up: > [image: Inline image 1] > > NuPIC could be used to predict the system outputs given the input/output > history. The search for the best inputs on the control horizon could be > done with a nonlinear least squares using a numerical derivative or some > global heuristic (such as an evolutionary strategy). This of course leads > to a local minimum, but sometimes this is more than enough. Learning would > be off during the search, and turned on only after the next input is chosen > and applied to the system. > > Is the CLA robust to white noise? Has anyone used NuPIC within a closed > stable loop? This actually changes the noise dynamics of the system, so I'm > not sure if the current learning algorithm can be applied indiscriminately. > > Do you think the current evaluation speed is fast enough for a local > search with numerical derivatives or a global heuristic search? On more > concrete terms, how long does it take to predict 30 time slices for 5 > outputs on a regular PC on a moderately sized network? > > The inputs and outputs are all real numbers, any idea on how to convert > this to a proper SDR? > > Thanks, > Pedro. > > -- > Pedro Tabacof, > State University of Campinas, Brazil. >
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