Pilot Inventory Complex Adaptive System : An Artificial Life Approach to Managing Pilot Retention
Language: English
Published by Legare Street Press Dez 2012, 2012
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - The retention of skilled pilots continues to be a problem that plagues the United States Air Force. After spending millions of dollars on training and education, it is disheartening to see the mass exodus of experienced aviators from the Air Force that has been occurring in the past decade. Many blame the economy, others the Air Force itself, but few are able to accurately predict how or why they are all leaving. The current personnel models do not adequately determine retention rates. Complex adaptive systems theory, however, might provide some insight. By modeling the system at the pilot's level, allowing each pilot to be represented as an autonomous, independent agent continually adapting to its environment and the other agents in it, an alternate model can be built; one that accounts for the interactions among the pilots, not just their interactions with their environment. PICAS (Pilot Inventory Complex Adaptive System) is just such a model. Constructed in the Java language, the PICAS model exploits the notions of complex adaptive systems theory and employs dynamic user controls to discern retention rates. Pilots 'evolve', for lack of a better word, to a greater fitness within their environment, and in the process the model user can better determine what kind of environment needs to be created and maintained in order to ensure that trained and experienced pilots are in fact retained for their services. This thesis will discuss the theory underlying the PICAS model, trace the development of the PICAS model, review the descriptive results the model produces, and finally investigate the uses of the model as a tool for exploratory modeling.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.…
Seller Inventory # 9781288414840
- Title
- Pilot Inventory Complex Adaptive System : An Artificial Life Approach to Managing Pilot Retention
- Author
- Martin P. Gaupp
- Publisher
- Legare Street Press Dez 2012
- Publication year
- 2012
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1288414846
- ISBN 13
- 9781288414840
- Item weight
- 235 grams
- Dimensions
- 234x156x9 mm
The retention of skilled pilots continues to be a problem that plagues the United States Air Force. After spending millions of dollars on training and education, it is disheartening to see the mass exodus of experienced aviators from the Air Force that has been occurring in the past decade. Many blame the economy, others the Air Force itself, but few are able to accurately predict how or why they are all leaving. The current personnel models do not adequately determine retention rates. Complex adaptive systems theory, however, might provide some insight. By modeling the system at the pilot's level, allowing each pilot to be represented as an autonomous, independent agent continually adapting to its environment and the other agents in it, an alternate model can be built; one that accounts for the interactions among the pilots, not just their interactions with their environment. PICAS (Pilot Inventory Complex Adaptive System) is just such a model. Constructed in the Java language, the PICAS model exploits the notions of complex adaptive systems theory and employs dynamic user controls to discern retention rates. Pilots 'evolve', for lack of a better word, to a greater fitness within their environment, and in the process the model user can better determine what kind of environment needs to be created and maintained in order to ensure that trained and experienced pilots are in fact retained for their services. This thesis will discuss the theory underlying the PICAS model, trace the development of the PICAS model, review the descriptive results the model produces, and finally investigate the uses of the model as a tool for exploratory modeling.
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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