Title :
Using hybrid knowledge bases for missile siting problems
Author :
Benton, John ; Subrahmanian, V.S.
Author_Institution :
Artificial Intelligence Div., US Army Topographic Eng. Center, Fort Belvoir, VA, USA
Abstract :
Hybrid knowledge bases (HKBs) are a formalism for integrating multiple representations of knowledge and data. HKBs provide a uniform framework for integrating uncertain information (as is often the case in terrain reasoning), temporal information (needed for weather effects, etc.), and numeric constraint solving capabilities (for situation assessment). We show how the HKB formalism may be applied to solve the problem of placing Patriot and Hawk missile batteries in a specified terrain, subject to the requirement that various existing assets be afforded maximal protection. We formalize this problem in a clear, mathematical framework, using the HKB paradigm, and show how the problem is solved. This provides a mathematically sound, as well as a practically viable, scalable solution to the important problem of missile siting
Keywords :
knowledge based systems; knowledge representation; military computing; missiles; Hawk missile batteries; Patriot missile batteries; asset protection; hybrid knowledge bases; missile siting problems; multiple knowledge representations; numeric constraint solving capabilities; scalable solution; situation assessment; temporal information; terrain reasoning; uncertain information; weather effects; Artificial intelligence; Batteries; Computer science; Deductive databases; Educational institutions; Gratings; Military computing; Missiles; Protection; Query processing;
Conference_Titel :
Artificial Intelligence for Applications, 1994., Proceedings of the Tenth Conference on
Conference_Location :
San Antonia, TX
Print_ISBN :
0-8186-5550-X
DOI :
10.1109/CAIA.1994.323681