While adaptive filtering is in principle intended for tracking non-stationary systems, most adaptive filtering algorithms have been designed for converging to a fixed unknown filter. When actually confronted with a non-stationary environment, they possess just one parameter (stepsize, forgetting factor) to adjust their tracking capability. Virtually the only existing optimal approach is the Kal...

To understand animals’ behavior in finding relations between similar tasks and adapting themselves to changes the tasks, it is necessary know how brain generalizes learned knowledge from a previous task unseen tasks. Recent studies neuroscience suggest that Successor Representation (SR)-based models provide adaptation goal locations or reward function faster than model-free algorithms, together...