A complex system is usually hard to describe, because it consists of several elements that interact with each other. Those interactions are often, and hence not directly proportional to their causes. Such complexity demands new approaches to design, control and optimize. This work explore the use of the COllective INtelligence (COIN) approach to address the challenges of the complex systems. A Collective is as a multi-agent system where each agent is self-interested, capable of learning. Also, the system has a well defined objective function that rates the performance of the Collective. To demonstrate and explore the potential of the COIN theory, three experiments were investigated. In the first experiment, we investigated the power of the COIN approach to optimize a variant of the congestion game with full communication level. In the second experiment, we investigated how the COIN approach behaves when there is a communication restriction among the agents. Finally, we applied the COIN theory to the network packet routing problem with different topologies.
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WAEL RASHWAN, MSc. is a PhD researcher in 3S Group (A research unit in College of Business - Dublin Institute of Technology (DIT) specialized in complex systems simulation and optimization). He joined the 3S (3sgroup.ie)in 2013. He has a B.Sc. and M.Sc. degree in operations research form Cairo University.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A complex system is usually hard to describe, because it consists of several elements that interact with each other. Those interactions are often, and hence not directly proportional to their causes. Such complexity demands new approaches to design, control and optimize. This work explore the use of the COllective INtelligence (COIN) approach to address the challenges of the complex systems. A Collective is as a multi-agent system where each agent is self-interested, capable of learning. Also, the system has a well de ned objective function that rates the performance of the Collective. To demonstrate and explore the potential of the COIN theory, three experiments were investigated. In the rst experiment, we investigated the power of the COIN approach to optimize a variant of the congestion game with full communication level. In the second experiment, we investigated how the COIN approach behaves when there is a communication restriction among the agents. Finally, we applied the COIN theory to the network packet routing problem with di erent topologies. 140 pp. Englisch. Codice articolo 9783639717341
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Rashwan WaelWAEL RASHWAN, MSc. is a PhD researcher in 3S Group (A research unit in College of Business - Dublin Institute of Technology (DIT) specialized in complex systems simulation and optimization). He joined the 3S (3sgroup.ie)i. Codice articolo 4999715
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Condizione: New. Print on Demand pp. 140 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Codice articolo 131377875
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Condizione: New. PRINT ON DEMAND pp. 140. Codice articolo 18128128262
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Collective Intelligence (COIN) | A Packet Routing Application | Wael Rashwan | Taschenbuch | 140 S. | Englisch | 2014 | Scholars' Press | EAN 9783639717341 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 105249221
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A complex system is usually hard to describe, because it consists of several elements that interact with each other. Those interactions are often, and hence not directly proportional to their causes. Such complexity demands new approaches to design, control and optimize. This work explore the use of the COllective INtelligence (COIN) approach to address the challenges of the complex systems. A Collective is as a multi-agent system where each agent is self-interested, capable of learning. Also, the system has a well de¿ned objective function that rates the performance of the Collective. To demonstrate and explore the potential of the COIN theory, three experiments were investigated. In the ¿rst experiment, we investigated the power of the COIN approach to optimize a variant of the congestion game with full communication level. In the second experiment, we investigated how the COIN approach behaves when there is a communication restriction among the agents. Finally, we applied the COIN theory to the network packet routing problem with di¿erent topologies.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Codice articolo 9783639717341
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A complex system is usually hard to describe, because it consists of several elements that interact with each other. Those interactions are often, and hence not directly proportional to their causes. Such complexity demands new approaches to design, control and optimize. This work explore the use of the COllective INtelligence (COIN) approach to address the challenges of the complex systems. A Collective is as a multi-agent system where each agent is self-interested, capable of learning. Also, the system has a well de ned objective function that rates the performance of the Collective. To demonstrate and explore the potential of the COIN theory, three experiments were investigated. In the rst experiment, we investigated the power of the COIN approach to optimize a variant of the congestion game with full communication level. In the second experiment, we investigated how the COIN approach behaves when there is a communication restriction among the agents. Finally, we applied the COIN theory to the network packet routing problem with di erent topologies. Codice articolo 9783639717341
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