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Applications of Information Systems to Homeland Security And Defense

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A range of threats in the areas of safety and security, from natural disasters to terrorism to conventional warfare, involve complex interactions that are beyond the scope and capabilities of traditional problem solving techniques. Applications of Information Systems to Homeland Security and Defense provides an overview of complex systems’ techniques, and presents both guidelines and specific instances of how they can be applied to security and defense applications. In today’s uncertain times, these techniques can provide a breakthrough in the capability to model, plan and respond to critical events in modern society.

Applications of Information Systems to Homeland Security and Defense is a must-read for anyone who is interested in the areas of security and defense, as well as for undergraduate and postgraduate students who are eager to learn about the applications of complex adaptive systems to real-life problems.

About the Author
Hussein A. Abbass is the directory of the Artificial Life and Adaptive Robotics Laboratory at the School of Information Technology and Electrical Engineering at the Australian Defense Force Academy campus of the University of New South Wales. Dr. Abbass is a Senior Member of the IEEE and has more than 15 years experience in industry and academia and more than a hundred fully refereed papers in international journals and conferences. He teaches computational intelligence related subjects and his research focuses on multi-agent systems, data mining, and artificial life models with applications to defence, security and business.

Daryl Essam is a lecturer at the School of Information Technology and Electrical Engineering at the Australian Defense Force Academy, campus of the University of New South Wales, where he teaches in multiple areas of computer science. Currently his research focuses on new algorithms for genetic programming, in particular the sub-fields of grammars, diversity, probabilistic approaches and multi-objective optimization.

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