Fuzzy logic-based system coordination by redundant symbolization and reduction of environmental complexities

In this paper, we will introduce the notion of system coordination with dynamical processes that are self-organized coordinatively via the interaction among system elements and external environments. First, a constraint-oriented interpretation of fuzzy set is introduced giving the notion of Constraint-Interval Fuzzy Set (CoIFS) in order to realize fuzzy logic-based coding of constraints yielding redundant symbolization and reduction of environmental complexities. Then, we will introduce Channel Theory to constraint-oriented fuzzy logic which provides us with a formal treatment of constraint propagation between fuzzy sets as Information Flow. Next, we will execute two kinds of computer simulation of constraint propagation as an approach to the system coordination; one is Constraint Propagation Dynamics without fuzzy logic-based coding of continuous variables yielding a stable property, and the other is Fuzzy Symbolic Dynamics with fuzzy label coding of continuous variables showing chaotic behaviors due to fluctuations caused by the fuzzy logic-based coding of variables into symbolic values (fuzzy labels).