A system and method for identifying and controlling an unknown dynamic system in which the system is identified, at least in part from test data, and a control scheme may be adapted on-line. In addition, the system may be used to develop an off-line solution to complex problems related to both dynamic and static systems. The system may use a multiprocessor architecture which may have a variety of configurations but is particularly suited for a neural network. The neural network may be built up of neurons that are either purely one way (forward signal path) or two way. Each neuron may be provided with its own synaptic weight, adjusted using only the local and backward signals.