Abstract
A fuzzy logic expert system has been developed that automatically allocates electronic attack resources on different platforms in real time. This 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 tree’s self-morphing property that increases its ability to adapt to changing events is discussed. The multi-platform tree allows a group of platforms to respond to a threat in a collaborative fashion. A genetic algorithm is used to optimize the resource manager. Experiments designed to test various concepts in the expert system are discussed, including its ability to: allow multiple platforms to self-organize without the benefit of a commander; to tolerate errors made by other systems; and to deal with multiple distinct enemy strategies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Schleher, D.C.: Electronic Warfare in the Information Age, Artech House, Boston, ch. 1 (1999)
Blackman, S., Popoli, R.: Design and Analysis of Modern Tracking Systems, ch. 11, Artech House, Boston (1999)
Tsoukalas, L.H., Uhrig, R.E.: Fuzzy and Neural Approaches in Engineering, ch. 5. John Wiley and Sons, New York (1997)
Holland, J.H.: Hidden Order How Adaptation Builds Complexity, pp. 1–15. Perseus Books, Reading (1995)
Zimmerman, H.J.: Fuzzy Set Theory and its Applications, ch. 1. Kluwer Academic Publishers Group, Boston (1991)
Smith III, J.F., Rhyne II, R.: A Resource Manager for Distributed Resources: Fuzzy Decision Trees and Genetic Optimization. In: Arabnia, H. (ed.) Proceedings of the International Conference on Artificial Intelligence, IC-AI 1999, vol. II, pp. 669–675. CSREA Press, Las Vegas (1999)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Smith III, J.F., Rhyne II, R.: Genetic Algorithm Based Optimization of a Fuzzy Logic Resource Manager: Data Mining and Co-evolution. In: Arabnia, H. (ed.) Proceeding of the International Conference on Artificial Intelligence, IC-AI 2000, vol. I, pp. 421–428. CSREA Press, Las Vegas (2000)
Smith III, J.F., Rhyne II, R.: A Fuzzy Logic Algorithm for Optimal Allocation of Distributed Resources. In: Bar Shalom, Y. (ed.) Fusion 1999: Proceedings of the Second International Conference on Information Fusion, International Society of Information Fusion, San Jose, pp. 402–409 (1999)
Smith III, J.F., Rhyne II, R.: Fuzzy logic based resource allocation for isolated and multiple platforms. In: Kadar, I. (ed.) Signal Processing, Sensor Fusion, and Target Recognition IX, vol. 4052, pp. 36–47. SPIE Proceedings, Orlando (2000)
Smith III, J.F., Rhyne II, R.: Genetic algorithm based optimization of a fuzzy logic resource manager for electronic attack. In: Dasarathy, B. (ed.) Data Mining and Knowledge Discovery II, vol. 4057, pp. 62–73. SPIE Proceedings, Orlando (2000)
Smith III, J.F., Rhyne II, R.: A Fuzzy Logic Resource Manager and Underlying Data Mining Techniques. In: Bar Shalom, Y. (ed.) Fusion 2000 Proceedings of the 3rd International Conference on Information Fusion. International Society of Information Fusion, Paris , vol. II (2000); WEB1-3 – WEB1-9
Smith III, J.F.: Co-evolutionary Data Mining to Discover Rules for Fuzzy Resource Management. In: Allison, N. (ed.) Proceedings of the International Conference for Intelligent Data Engineering and Automated Learning, pp. 19–24. Springer, Manchester (2002)
Smith III, J.F.: Fuzzy Logic Resource Manager: Evolving Fuzzy Decision Tree Structure that Adapts in Real-Time. In: Li, X. (ed.) Proceedings of the International Society of Information Fusion 2003, pp. 838–845. International Society of Information Fusion Press, Cairns (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Smith, J.F. (2005). Fuzzy Logic Resource Manager: Fuzzy Rules and Experiments. In: Bandini, S., Manzoni, S. (eds) AI*IA 2005: Advances in Artificial Intelligence. AI*IA 2005. Lecture Notes in Computer Science(), vol 3673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558590_57
Download citation
DOI: https://doi.org/10.1007/11558590_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29041-4
Online ISBN: 978-3-540-31733-3
eBook Packages: Computer ScienceComputer Science (R0)