Abstract
A fuzzy logic expert system has been developed that automatically allocates resources in real-time over a collection of autonomous agents. 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 four trees, the isolated platform tree, the multi-platform tree, the fuzzy parameter selection tree and the fuzzy strategy tree. The isolated platform tree provides a fuzzy decision tree that allows an individual platform to respond to a threat. The multi-platform tree allows a group of platforms to respond to a threat in a collaborative self-organizing fashion. The fuzzy parameter selection tree is designed to make optimal selections of root concept parameters. The strategy tree is a fuzzy tree that an agent uses to try to predict the behavior of an enemy. Finally, the five approaches to validating the expert system are discussed.
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© 2002 Springer-Verlag Berlin Heidelberg
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Smith, J.F. (2002). Multi-agent Fuzzy Logic Resource Manager. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_38
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DOI: https://doi.org/10.1007/3-540-45675-9_38
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