Cooperative Control and Optimization:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
2002
|
| Schriftenreihe: | Applied Optimization
66 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | A cooperative system is defined to be multiple dynamic entities that share information or tasks to accomplish a common, though perhaps not singular, objective. Examples of cooperative control systems might include: robots operating within a manufacturing cell, unmanned aircraft in search and rescue operations or military surveillance and attack missions, arrays of micro satellites that form a distributed large aperture radar, employees operating within an organization, and software agents. The term entity is most often associated with vehicles capable of physical motion such as robots, automobiles, ships, and aircraft, but the definition extends to any entity concept that exhibits a time dependent behavior. Critical to cooperation is communication, which may be accomplished through active message passing or by passive observation. It is assumed that cooperation is being used to accomplish some common purpose that is greater than the purpose of each individual, but we recognize that the individual may have other objectives as well, perhaps due to being a member of other caucuses. This implies that cooperation may assume hierarchical forms as well. The decision-making processes (control) are typically thought to be distributed or decentralized to some degree. For if not, a cooperative system could always be modeled as a single entity. The level of cooperation may be indicated by the amount of information exchanged between entities. Cooperative systems may involve task sharing and can consist of heterogeneous entities. Mixed initiative systems are particularly interesting heterogeneous systems since they are composed of humans and machines. Finally, one is often interested in how cooperative systems perform under noisy or adversary conditions. In December 2000, the Air Force Research Laboratory and the University of Florida successfully hosted the first Workshop on Cooperative Control and Optimization in Gainesville, Florida. This book contains selected refereed papers summarizing the participants' research in control and optimization of cooperative systems. Audience: Faculty, graduate students, and researchers in optimization and control, computer sciences and engineering |
| Beschreibung: | 1 Online-Ressource (XII, 308 p) |
| ISBN: | 9780306475368 9781402005497 |
| ISSN: | 1384-6485 |
| DOI: | 10.1007/b130435 |
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| 500 | |a A cooperative system is defined to be multiple dynamic entities that share information or tasks to accomplish a common, though perhaps not singular, objective. Examples of cooperative control systems might include: robots operating within a manufacturing cell, unmanned aircraft in search and rescue operations or military surveillance and attack missions, arrays of micro satellites that form a distributed large aperture radar, employees operating within an organization, and software agents. The term entity is most often associated with vehicles capable of physical motion such as robots, automobiles, ships, and aircraft, but the definition extends to any entity concept that exhibits a time dependent behavior. Critical to cooperation is communication, which may be accomplished through active message passing or by passive observation. | ||
| 500 | |a It is assumed that cooperation is being used to accomplish some common purpose that is greater than the purpose of each individual, but we recognize that the individual may have other objectives as well, perhaps due to being a member of other caucuses. This implies that cooperation may assume hierarchical forms as well. The decision-making processes (control) are typically thought to be distributed or decentralized to some degree. For if not, a cooperative system could always be modeled as a single entity. The level of cooperation may be indicated by the amount of information exchanged between entities. Cooperative systems may involve task sharing and can consist of heterogeneous entities. Mixed initiative systems are particularly interesting heterogeneous systems since they are composed of humans and machines. Finally, one is often interested in how cooperative systems perform under noisy or adversary conditions. | ||
| 500 | |a In December 2000, the Air Force Research Laboratory and the University of Florida successfully hosted the first Workshop on Cooperative Control and Optimization in Gainesville, Florida. This book contains selected refereed papers summarizing the participants' research in control and optimization of cooperative systems. Audience: Faculty, graduate students, and researchers in optimization and control, computer sciences and engineering | ||
| 650 | 4 | |a Mathematics | |
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Datensatz im Suchindex
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| discipline | Mathematik |
| doi_str_mv | 10.1007/b130435 |
| format | Electronic eBook |
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| isbn | 9780306475368 9781402005497 |
| issn | 1384-6485 |
| language | English |
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| spelling | Murphey, Robert Verfasser aut Cooperative Control and Optimization edited by Robert Murphey, Panos M. Pardalos Boston, MA Springer US 2002 1 Online-Ressource (XII, 308 p) txt rdacontent c rdamedia cr rdacarrier Applied Optimization 66 1384-6485 A cooperative system is defined to be multiple dynamic entities that share information or tasks to accomplish a common, though perhaps not singular, objective. Examples of cooperative control systems might include: robots operating within a manufacturing cell, unmanned aircraft in search and rescue operations or military surveillance and attack missions, arrays of micro satellites that form a distributed large aperture radar, employees operating within an organization, and software agents. The term entity is most often associated with vehicles capable of physical motion such as robots, automobiles, ships, and aircraft, but the definition extends to any entity concept that exhibits a time dependent behavior. Critical to cooperation is communication, which may be accomplished through active message passing or by passive observation. It is assumed that cooperation is being used to accomplish some common purpose that is greater than the purpose of each individual, but we recognize that the individual may have other objectives as well, perhaps due to being a member of other caucuses. This implies that cooperation may assume hierarchical forms as well. The decision-making processes (control) are typically thought to be distributed or decentralized to some degree. For if not, a cooperative system could always be modeled as a single entity. The level of cooperation may be indicated by the amount of information exchanged between entities. Cooperative systems may involve task sharing and can consist of heterogeneous entities. Mixed initiative systems are particularly interesting heterogeneous systems since they are composed of humans and machines. Finally, one is often interested in how cooperative systems perform under noisy or adversary conditions. In December 2000, the Air Force Research Laboratory and the University of Florida successfully hosted the first Workshop on Cooperative Control and Optimization in Gainesville, Florida. This book contains selected refereed papers summarizing the participants' research in control and optimization of cooperative systems. Audience: Faculty, graduate students, and researchers in optimization and control, computer sciences and engineering Mathematics Information theory Electronic data processing Computational complexity Systems theory Mathematical optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Theory of Computation Numeric Computing Discrete Mathematics in Computer Science Datenverarbeitung Mathematik Kooperatives Informationssystem (DE-588)4681247-7 gnd rswk-swf Adaptivregelung (DE-588)4000457-0 gnd rswk-swf 1\p (DE-588)1071861417 Konferenzschrift 2000 Gainesville Fla. gnd-content Kooperatives Informationssystem (DE-588)4681247-7 s Adaptivregelung (DE-588)4000457-0 s 2\p DE-604 Pardalos, Panos M. Sonstige oth https://doi.org/10.1007/b130435 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Murphey, Robert Cooperative Control and Optimization Mathematics Information theory Electronic data processing Computational complexity Systems theory Mathematical optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Theory of Computation Numeric Computing Discrete Mathematics in Computer Science Datenverarbeitung Mathematik Kooperatives Informationssystem (DE-588)4681247-7 gnd Adaptivregelung (DE-588)4000457-0 gnd |
| subject_GND | (DE-588)4681247-7 (DE-588)4000457-0 (DE-588)1071861417 |
| title | Cooperative Control and Optimization |
| title_auth | Cooperative Control and Optimization |
| title_exact_search | Cooperative Control and Optimization |
| title_full | Cooperative Control and Optimization edited by Robert Murphey, Panos M. Pardalos |
| title_fullStr | Cooperative Control and Optimization edited by Robert Murphey, Panos M. Pardalos |
| title_full_unstemmed | Cooperative Control and Optimization edited by Robert Murphey, Panos M. Pardalos |
| title_short | Cooperative Control and Optimization |
| title_sort | cooperative control and optimization |
| topic | Mathematics Information theory Electronic data processing Computational complexity Systems theory Mathematical optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Theory of Computation Numeric Computing Discrete Mathematics in Computer Science Datenverarbeitung Mathematik Kooperatives Informationssystem (DE-588)4681247-7 gnd Adaptivregelung (DE-588)4000457-0 gnd |
| topic_facet | Mathematics Information theory Electronic data processing Computational complexity Systems theory Mathematical optimization Calculus of Variations and Optimal Control; Optimization Systems Theory, Control Theory of Computation Numeric Computing Discrete Mathematics in Computer Science Datenverarbeitung Mathematik Kooperatives Informationssystem Adaptivregelung Konferenzschrift 2000 Gainesville Fla. |
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