Predicting NN5 Time Series with Neurosolver
Neurosolver is a neuromorphic planner and a problem solving system. It was tested on several problem solving and planning tasks such as rearranging blocks and controlling a software-simulated artificial rat running in a maze. In these tasks, the Neurosolver created models of the problem as temporal patterns in the problem space. These behavioral traces were then used to perform searches and generate actions. In this paper, we present an analysis of the capabilities of the Neurosolver to predict data points in time series. We report on testing those capabilities on the sample data sets that were made available for the neural network forecasting competition NN5 [14]. We conclude with a brief description of several ideas that we are currently applying to the data sets posted for the 2010 competition, NN GC1.
neural network forecasting neuromorphic systems general problem solvers predicting future behavioral patterns