Buch, Englisch, Band 11, 271 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Buch, Englisch, Band 11, 271 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Reihe: Genetic Algorithms and Evolutionary Computation
ISBN: 978-1-4757-8494-7
Verlag: Springer US
Frontiers of Evolutionary Computation brings together eleven contributions by international leading researchers discussing what significant issues still remain unresolved in the field of Evolutionary Computation (EC). They explore such topics as the role of building blocks, the balancing of exploration with exploitation, the modeling of EC algorithms, the connection with optimization theory and the role of EC as a meta-heuristic method, to name a few. The articles feature a mixture of informal discussion interspersed with formal statements, thus providing the reader an opportunity to observe a wide range of EC problems from the investigative perspective of world-renowned researchers. These prominent researchers include:
-Heinz Mühlenbein,
-Kenneth De Jong,
-Carlos Cotta and Pablo Moscato,
-Lee Altenberg,
-Gary A. Kochenberger, Fred Glover, Bahram Alidaee and Cesar Rego,
-William G. Macready,
-Christopher R. Stephens and Riccardo Poli,
-Lothar M. Schmitt,
-John R. Koza, Matthew J. Street and Martin A. Keane,
-Vivek Balaraman,
-Wolfgang Banzhaf and Julian Miller.
Frontiers of Evolutionary Computation is ideal for researchers and students who want to follow the process of EC problem-solving and for those who want to consider what frontiers still await their exploration.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
Weitere Infos & Material
Towards A Theory of Organisms and Evolving Automata.- Two Grand Challenges for EC.- Evolutionary Computation: Challenges and Duties.- Open Problems in the Spectral Analysis of Evolutionary Dynamics.- Solving Combinatorial Optimization Problems Via Reformulation and Adaptive Memory Metaheuristics.- Problems in Optimization.- EC Theory — “in Theory”.- Asymptotic Convergence of Scaled Genetic Algorithms to Global Optima.- The Challenge of Producing Human-Competitive Results by Means of Genetic and Evolutionary Computation.- Case Based Reasoning.- The Challenge of Complexity.