A fuzzy logic resource manager and underlying data mining techniques

A fuzzy logic-based expert system has been developed that automatically allocates electronic attack (EA) resources in real-time over many dissimilar platforms. The platforms can be very general, eg. ships, planes, robots, land-based facilities, etc. The potential foes the platforms deal with can also be general. This paper describes data mining activities related to development of the resource manager, with a focus on genetic algorithm-based optimization. The use of a database of scenarios prevents the algorithm from having too narrow a range of behaviors, i.e. it creates a more robust solution. The approach to optimization is a type of co-evolution, i.e. both friend and foe agents simultaneously adapt within a complicated environment perceived through various sensors, such as radar, electronic support measures, etc. New rule classes and the five components of the resource manager are discussed. Finally, the resource manager´s multi-platform response is examined for multiple scenarios.