1. A stochastic signal processing system configured to implement task-specific learning, the system comprising: a controller apparatus configured to generate an output control signal based on an input signal, the controller apparatus being characterized by a controller state parameter and a control parameter; and a learning apparatus configured to: generate an adjustment signal based on the input signal, the controller state parameter, and the output control signal; and provide the adjustment signal to the controller apparatus, thereby effectuating learning; wherein: the control parameter is configured in accordance with a task; the adjustment signal is configured to modify the control parameter based on the input signal and the output control signal; the adjustment signal is determined as a product of a controller performance function with a gradient of a per-stimulus entropy parameter, the gradient being determined based on the control parameter; the per-stimulus entropy parameter h is configured to characterize a dependence of the output control signal on (i) the input signal and (ii) the control parameter; and the per-stimulus entropy parameter is determined based on a natural logarithm of p(y|x,w), where p denotes a conditional probability of the output control signal y given the input signal x with respect to the control parameter w.