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The work human decision makers onboard naval platforms have to perform is becoming more demanding due to new types of missions as well as advanced warplanes, more accurate weapons, and long-range sensors. Hence, providing operators with adequate support is an essential requirement for future Navy C2 systems. Because of the high complexity of most operator tasks full automation is not advisable. The final decisions must be made by human operators. Appropriately helping them to create a correct understanding of the situation can make the difference between a catastrophe and doing exactly the right thing. Some particular behavior patterns can be modeled best by rule-based AI, for others more sophisticated approaches have to be considered. Five techniques are described within this paper, whereof three shall be deemed to be potential constituents of the aspired support system. They all have in common that enfolding case-bases are needed to become able to apply them beneficially. A conceivable way to obtain such a case-base is empirical knowledge acquisition by means of a laboratory test bed. Furthermore, means to structure the so-elicited knowledge have to be chosen and evaluated. Utilizing the methodology introduced here could yield helpful support for AAW operators, but yet there is much more research to be done., See also ADM001577. The original document contains color images.