1. A fuzzy logic decision-maker for receiving input signals, utilizing data in a knowledge-base and, based on said input signals and said data, providing output signals in order to provide knowledge-based decision making, said knowledge-base of the type containing fuzzy rules comprising representations of fuzzy patterns of consequents (THENs) and representations of fuzzy patterns of antecedents (IFs); clearness distributions comprising collections of representations of clearness degrees, said clearness degrees defining cognitive measures which assess the fuzziness of fuzzy patterns, and representations of thresholds of transitions, said thresholds of transitions being the intersection points of every two adjacent clearness distributions, said fuzzy logic decision-maker comprising: a fuzzifier comprising first means for mapping said input signals into representations of input fuzzy patterns and second means for mapping said input signals into representations of input clearness degrees of said input fuzzy patterns, said input clearness degrees being valued in the interval of zero to one, where zero represents "absolutely unclear" ("absolutely false") and one represents "absolutely clear" ("absolutely true"); pattern matching and rule selection means for receiving said representations of input fuzzy patterns from said first means of said fuzzifier and, responsive thereto, for selecting one rule from said knowledge-base, and for generating representations of output fuzzy patterns based on the consequent (THEN) portion of said rule; approximate reasoning means for receiving said representations of input clearness degrees from said second means of said fuzzifier and for mapping said representations of input clearness degrees into a representation of an output clearness degree, said approximate reasoning means operating in parallel with said pattern matching and rule selection means; and defuzzifier means for receiving said representations of output fuzzy patterns from said pattern matching and rule selection means and for receiving said representation of an output clearness degree from said approximate reasoning means and for mapping said representations of output fuzzy patterns and said representation of an output clearness degree into said output signals.
9. The fuzzy logic decision-maker of claim 1 wherein said representations of input fuzzy patterns comprise indices, names, or addresses of said input fuzzy patterns and wherein said representations of output fuzzy patterns comprise indices, names, or addresses of said output fuzzy patterns.