Introduction

When we have multiple situations with several different analysis results, we often need to choose a situation or result that will lead us to our desired goal with reasonable accuracy. We need to use available knowledge and information as well as logic or a statistical method to arrive at an appropriate decision. Decision making is often (and perhaps always) coupled with knowledge representation, which is derived through an inference process or engine, operating with the measured data or collected raw information. In Part II, we emphasize the use of fuzzy logic (Type I FL/S; see Epilogue) for decision making and fusion.