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Title Knowledge incorporation in evolutionary computation / Yaochu Jin (ed.)
Published Berlin ; New York : Springer, [2005]
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Description 1 online resource (xiii, 548 pages) : illustrations
Series Studies in fuzziness and soft computing, 1434-9992 ; v. 167
Studies in fuzziness and soft computing ; v. 167
Contents Introduction -- A Selected Introduction to Evolutionary Computation / Xin Yao -- The Use of Collective Memory in Genetic Programming / Keith Bearpark, Andy J. Keane -- A Cultural Algorithm for Solving the Job Shop Scheduling Problem / Ricardo Landa Becerra, Carlos A. Coello Coello -- Case-Initialized Genetic Algorithms for Knowledge Extraction and Incorporation / Judy Johnson, Sushil J. Louis -- Using Cultural Algorithms to Evolve Strategies in A Complex Agent-based System / David A. Ostrowski, Robert G. Reynolds -- Methods for Using Surrogate Models to Speed Up Genetic Algorithm Optimization: Informed Operators and Genetic Engineering / Khaled Rasheed, Xiao Ni, Swaroop Vattam -- Fuzzy Knowledge Incorporation in Crossover and Mutation / Jun Zhang, Henry S.H. Chung, Alan W.L. Lo, B.J. Hu -- Learning Probabilistic Models for Enhanced Evolutionary Computation / Peter A.N. Bosman, Dirk Thierens
Probabilistic Models for Linkage Learning in Forest Management / Els I. Ducheyne, B. De Baets, R. De Wulf -- Performance-Based Computation of Chromosome Lifetimes in Genetic Algorithms / Adnan Acan, Yüce Tekol -- Genetic Algorithm and Case-Based Reasoning Applied in Production Scheduling / Pei-Chann Chang, Jih-Chang Hsieh, Yen-Wen Wang -- Knowledge-Based Evolutionary Search for Inductive Concept Learning / Federico Divina, Elena Marchiori -- An Evolutionary Algorithm with Tabu Restriction and Heuristic Reasoning for Multiobjective Optimization / E.F. Khor, K.C. Tan, Y.J. Yang -- Neural Networks for Fitness Approximation in Evolutionary Optimization / Yaochu Jin, Michael Hüsken, Markus Olhofer, Bernhard Sendhoff -- Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems / Yew Soon Ong, P.B. Nair, A.J. Keane, K.W. Wong -- Model Assisted Evolution Strategies / Holger Ulmer, Felix Streichert, Andreas Zell
Knowledge Incorporation Through Lifetime Learning / Kim W.C. Ku, M.W. Mak -- Local Search Direction for Multi-Objective Optimization Using Memetic EMO Algorithms / Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi -- Fashion Design Using Interactive Genetic Algorithm with Knowledge-based Encoding / Hee-Su Kim, Sung-Bae Cho -- Interactive Evolutionary Design / Ian C. Parmee, Johnson A. Abraham -- Preference Incorporation in Multi-objective Evolutionary Computation -- Integrating User Preferences into Evolutionary Multi-Objective Optimization / Jürgen Branke, Kalyanmoy Deb -- Human Preferences and their Applications in Evolutionary Multi--Objective Optimization / Dragan Cvetković, Carlos A. Coello Coello -- An Interactive Fuzzy Satisficing Method for Multiobjective Integer Programming Problems through Genetic Algorithms / Kosuke Kato, Cahit Perkgoz, Masatoshi Sakawa -- Interactive Preference Incorporation in Evolutionary Engineering Design / Jiachuan Wang, Janis P. Terpenny
Summary This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge representation methods. "Knowledge Incorporation in Evolutionary Computation" is a valuable reference for researchers, students and professionals from engineering and computer science, in particular in the areas of artificial intelligence, soft computing, natural computing, and evolutionary computation
Bibliography Includes bibliographical references and index
Notes Print version record
Subject Evolutionary programming (Computer science)
Evolutionary computation.
Genre/Form Ebook.
Form Electronic book
Author Jin, Yaochu, 1966-
ISBN 3540445110 (electronic bk.)
3642061745 (print)
9783540445111 (electronic bk.)
9783642061745 (print)
(alk. paper)
(alk. paper)