An RBF network alternative for a hybrid architecture
Todd Peterson, Ruiji Sun · 2002
Although our previous model CLARION has shown some measure of success in reactive sequential decision making tasks by utilizing a hybrid architecture which uses both procedural and declarative learning, it suffers from a number of problems because of its use of backpropagation networks. CLARION-RBF is a more parsimonious architecture that remedies some of the problems exhibited in CLARION by utilizing RBF Networks. CLARION-RBF is also capable of learning reactive procedures, and can have high level symbolic knowledge extracted and applied.