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Learning and Intelligent Optimization [electronic resource] : 9th International Conference, LION 9, Lille, France, January 12-15, 2015. Revised Selected Papers / edited by Clarisse Dhaenens, Laetitia Jourdan, Marie-Eléonore Marmion.

Contributor(s): Dhaenens, Clarisse [editor.] | Jourdan, Laetitia [editor.] | Marmion, Marie-Eléonore [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Theoretical Computer Science and General Issues: 8994Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015.Description: XI, 313 p. 92 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319190846.Subject(s): Algorithms | Computer science | Artificial intelligence | Numerical analysis | Computer simulation | Algorithms | Computer Science Logic and Foundations of Programming | Artificial Intelligence | Numerical Analysis | Theory of Computation | Computer ModellingAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 518.1 Online resources: Click here to access online
Contents:
Benchmark problems and performance measures -- Tracking moving optima -- Dynamic multiobjective optimization -- Adaptation, learning, and anticipation -- Handling noisy fitness functions -- Using fitness approximations -- Searching for robust optimal solutions -- Comparative studies -- Hybrid approaches -- Theoretical analysis -- Real-world applications.
In: Springer Nature eBookSummary: This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as benchmark problems and performance measures; tracking moving optima; dynamic multiobjective optimization; adaptation, learning, and anticipation; handling noisy fitness functions; using fitness approximations; searching for robust optimal solutions; comparative studies; hybrid approaches; theoretical analysis; and real-world applications.
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Benchmark problems and performance measures -- Tracking moving optima -- Dynamic multiobjective optimization -- Adaptation, learning, and anticipation -- Handling noisy fitness functions -- Using fitness approximations -- Searching for robust optimal solutions -- Comparative studies -- Hybrid approaches -- Theoretical analysis -- Real-world applications.

This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization, LION 9, which was held in Lille, France, in January 2015. The 31 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as benchmark problems and performance measures; tracking moving optima; dynamic multiobjective optimization; adaptation, learning, and anticipation; handling noisy fitness functions; using fitness approximations; searching for robust optimal solutions; comparative studies; hybrid approaches; theoretical analysis; and real-world applications.

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