Abstract
An NPN (Negative-Positive-Neutral) fuzzy set theory and an NPN qualitative algebra (Q-algebra) are proposed which form a computational framework for bipolar cognitive modeling and multiagent decision analysis. First a 6-valued NPN logic is introduced which extends the usual 4-valued Q-algebra (S, approximately , plus sign in circle,multiply sign in circle) and S={+,-,0,?} by adding one more level of specification; and then a real-valued NPN fuzzy logic is introduced which extends the 6-valued model to the real space { for all(x,y)|(x,y)in[-1,0]x[0,1]} and adds infinite levels of specifications, As a generalization, a fuzzy set theory is presented that allows beta-level fuzzy number-based NPN variables (x,y) to be substituted into (S, approximately , plus sign in circle,multiply sign in circle) where multiply sign in circle stands for any NPN T-norm; plus sign in circle stands for disjunction (V) or union ( union or logical sum), and beta is the number of alpha-cuts.
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