Synopsis
Distributed constraint optimization (DCOP) is a model where several agents coordinate with each other to take on values so as to minimize the sum of the resulting constraint costs, which are dependent on the values of the agents. This model is becoming popular for formulating and solving multi-agent coordination problems. As a result, researchers have developed a class of DCOP algorithms that use search techniques. Since solving DCOP problems optimally is NP-hard, solving large problems efficiently becomes an issue. In this book, I show how one can speed up DCOP search algorithms by applying insights gained from centralized search algorithms, specifically by using an appropriate search strategy; by sacrificing solution optimality; by using more memory; and by reusing information gained from solving similar DCOP problems.
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About the Author
William Yeoh is an assistant professor of computer science at New Mexico State University. He received his Ph.D. in computer science at the University of Southern California. His research interests include multi-agent systems, distributed constraint reasoning, heuristic search, and planning with uncertainty.
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Speeding Up Distributed Constraint Optimization Search Algorithms
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ISBN 10: 3639707214
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Distributed constraint optimization (DCOP) is a model where several agents coordinate with each other to take on values so as to minimize the sum of the resulting constraint costs, which are dependent on the values of the agents. This model is becoming popular for formulating and solving multi-agent coordination problems. As a result, researchers have developed a class of DCOP algorithms that use search techniques. Since solving DCOP problems optimally is NP-hard, solving large problems efficiently becomes an issue. In this book, I show how one can speed up DCOP search algorithms by applying insights gained from centralized search algorithms, specifically by using an appropriate search strategy; by sacrificing solution optimality; by using more memory; and by reusing information gained from solving similar DCOP problems. 196 pp. Englisch. Seller Inventory # 9783639707212
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yeoh WilliamWilliam Yeoh is an assistant professor of computer science at New Mexico State University. He received his Ph.D. in computer science at the University of Southern California. His research interests include multi-agent sys. Seller Inventory # 4999056
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Taschenbuch. Condition: Neu. Speeding Up Distributed Constraint Optimization Search Algorithms | William Yeoh | Taschenbuch | 196 S. | Englisch | 2014 | Scholars' Press | EAN 9783639707212 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 105497485
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Speeding Up Distributed Constraint Optimization Search Algorithms
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ISBN 10: 3639707214
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Distributed constraint optimization (DCOP) is a model where several agents coordinate with each other to take on values so as to minimize the sum of the resulting constraint costs, which are dependent on the values of the agents. This model is becoming popular for formulating and solving multi-agent coordination problems. As a result, researchers have developed a class of DCOP algorithms that use search techniques. Since solving DCOP problems optimally is NP-hard, solving large problems efficiently becomes an issue. In this book, I show how one can speed up DCOP search algorithms by applying insights gained from centralized search algorithms, specifically by using an appropriate search strategy; by sacrificing solution optimality; by using more memory; and by reusing information gained from solving similar DCOP problems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch. Seller Inventory # 9783639707212
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Distributed constraint optimization (DCOP) is a model where several agents coordinate with each other to take on values so as to minimize the sum of the resulting constraint costs, which are dependent on the values of the agents. This model is becoming popular for formulating and solving multi-agent coordination problems. As a result, researchers have developed a class of DCOP algorithms that use search techniques. Since solving DCOP problems optimally is NP-hard, solving large problems efficiently becomes an issue. In this book, I show how one can speed up DCOP search algorithms by applying insights gained from centralized search algorithms, specifically by using an appropriate search strategy; by sacrificing solution optimality; by using more memory; and by reusing information gained from solving similar DCOP problems. Seller Inventory # 9783639707212
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