A fuzzy logic algorithm has been developed that automatically allocates electronic attack resources distributed over different platforms in real-time. The controller must be able to make decisions based on rules provided by experts. The fuzzy logic approach allows the direct incorporation of expertise. Genetic algorithm based optimization is conducted to determine the form of the membership functions for the fuzzy root concepts. The resource manager is made up of five parts, the isolated platform model, the multi-platform model, the fuzzy EA model, the fuzzy parameter selection tree and the fuzzy strategy tree. Automatic determination of fuzzy decision tree topology using a genetic program, an algorithm that uses the theory of evolution to create other algorithms is discussed. A tree originally obtained from expertise is compared to a tree evolved using a genetic program. The tree created by the genetic program is superior for some applications to one constructed solely based on expertise. The concept of self-morphing trees, i.e., decision trees that can change their own computational complexity in real-time is introduced. The strategy tree concept and how various fuzzy concepts overlap in phase space to create a more robust resource manager are considered. Finally, methods of validating the algorithm are discussed.


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    Title :

    Fuzzy logic resource manager: decision tree topology, combined admissible regions, and the self-morphing property


    Contributors:


    Publication date :

    2003


    Size :

    11 Seiten, 12 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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