The work in this book is based on philosophical as well as logical views on the subject of
decoding the 'progress' of decision making process in the cognition system of a decision maker
(be it a human or an animal or a bird or any living thing which has a brain) while evaluating
the membership value µ(x) in a fuzzy set or in an intuitionistic fuzzy set or in any such soft
computing set model or in a crisp set. A new theory is introduced called by Theory of CIFS. The
following two hypothesis are hidden facts in fuzzy computing or in any soft computing process
:- Fact-1: A decision maker (intelligent agent) can never use or apply 'fuzzy theory' or any
soft-computing set theory without intuitionistic fuzzy system.Fact-2 : The Fact-1 does not
necessarily require that a fuzzy decision maker (or a crisp ordinary decision maker or a
decision maker with any other soft theory models or a decision maker like animal bird which has
brain etc.) must be aware or knowledgeable about IFS Theory! The Theory of CIFS is developed
with a careful analysis unearthing the correctness of these two facts. Two examples of
'decision making problems' with complete solutions are presented out of which one example will
show the dominance of the application potential of intuitionistic fuzzy set theory over fuzzy
set theory and the other will show the converse i.e. the dominance of the application
potential of fuzzy set theory over intuitionistic fuzzy set theory in some cases. The Theory of
CIFS may be viewed to belong to the subjects : Theory of Intuitionistic Fuzzy Sets Soft
Computing Artificial Intelligence etc.
