Reducing Uncertainty in Effects Based Operations

Bol

Known as the fog of war, uncertainty has been prevalent in the conduct of military operations throughout human history. Intelligence collection efforts are tasked to reduce this uncertainty through the collection of information. Utilizing Shannon's entropy as a measure of the expected information gain due to an intelligence collection effort, a methodology is developed to prioritize and allocate intelligence assets in an efficient manner. Incorporated in this methodology are target priority and the requirement to reassess dynamic targets. The application area for the methodology is Effects-Based Operations. A generalized state model is developed to conduct adversary system-of-systems analysis. This model forms the basis for the entropy calculations and the resultant integer program to maximize the information gain.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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Pages: 110, Hardcover, Hutson Street Press