Maintaining genetic diversity in genetic algorithms through co-evolution-Reference-Cited by-同舟云学术

Maintaining genetic diversity in genetic algorithms through co-evolution

Published:1998 Issue: Volume: Page:128-138
ISSN:0302-9743
Container-title:Advances in Artificial Intelligence
language:
Short-container-title:

Author:

Morrison Jason,Oppacher Franz

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-64575-6_45

Reference13 articles.

1. P. J. Angeline and J. B. Pollack. Competitive Environments Evolve Better Solutions for Complex Tasks. In Fifth International Conference on Genetic Algorithms, pages 264–270, 1993.

2. J. E. Baker. Adative Selection Methods for Genetic Algorithms. In J. J. Grefenstette, editor, International Conference on Genetic Algorithms: ICGA'85, pages 101–106, 1985.

3. K. Deb and D. E. Goldberg. An Investigation of Niche and Species Formation in Genetic Function Optimization. In J. D. Schaffer, editor, International Conference on Genetic Algorithms. ICCA'89, pages 42–43, 1989.

4. W. D. Hillis. Co-evolving parasites improve simulated evolution as an optimization procedure. In Artificial Life II, SPY Studies in the Sciences of Complexity, volume 10, pages 313–323.

5. J. H. Holland. Royal roads functions. Internet Genetic Algorithms Digest, 7:issue 22, August 12 1993.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Hardware-based Evolutionary Algorithm with Multi-Objective Optimization Operators for On-Chip Transient Fault Detection;2022 IEEE 40th VLSI Test Symposium (VTS);2022-04-25

2. An enhanced genetic algorithm for solving learning path adaptation problem;Education and Information Technologies;2021-04-08

3. Diversity in Search-Based Unit Test Suite Generation;Search Based Software Engineering;2017

4. Multi-Objective Probability Collectives;Applications of Evolutionary Computation;2010