"Ignorance-based" systems
A. S. Gevins, N. Morgan · 2005
Recent work in artificial intelligence and signal processing has suggested that a merger of the two fields would be profitable for both (Kopec et al, 1982). Here we discuss the improvement of decision systems by the use of iterative mathematical techniques. These techniques could be called "ignorance-based" since they can be characterized by exhaustive searches for useful combinations of problem-relevant variables in data spaces for which human knowledge is incomplete.