Impact of regulatory genes on optimization behavior

2012 IEEE Congress on Evolutionary Computation, CEC 2012

Volumn , Issue , 2012, Pages

  Ashlock, Daniel ^a   Ashlock, Wendy ^b  

^a UNIVERSITY OF GUELPH   (Canada)

^b YORK UNIVERSITY   (Canada)

Author keywords

Evolutionary Optimization; Nature Inspired Algorithms; Representation

Indexed keywords

DELETION MUTATIONS; EVOLUTIONARY OPTIMIZATIONS; FITNESS LANDSCAPE; LINEAR REPRESENTATION; NATURE INSPIRED ALGORITHMS; NEGATIVE CONTROL; OPTIMIZATION PROBLEMS; REGULATORY GENES; REGULATORY MECHANISM; REPRESENTATION; SEARCH SPACES; UNIMODAL;

OPTIMIZATION;

GENES;

EID: 84866848747     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2012.6252981     Document Type: Conference Paper

References (23)

1. D. Ashlock. Evolutionary Computation for Modeling and Optimization. Springer, New York, 2006.
2. D. Ashlock and W. Ashlock. Simulation of the impact of retroviruses on genome organization of an artificial organism. In IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pages 140-146, 2009.
3. D. Ashlock and M. Joenks. ISAc lists, a different representation for program induction. In Genetic Programming 98, proceedings of the third annual genetic programming conference., pages 3-10, San Francisco, 1998. Morgan Kaufmann.
4. D. Ashlock, C. Lee, and C. McGuinness. Search-based procedural generation of maze-like levels. 3(3):260-273, 2011.
5. D. Ashlock and A. McEachern. Ring optimization of side effect machines. In Intelligent Engineering Systems Through Artificial Neural Networks, 19, pages 165-172, 2009.
6. D. Ashlock and A. Sherk. Non-local adaptation of artificial predators and prey. In Proceedings of the 2005 Congress on Evolutionary Computation, volume 1, pages 98-105. IEEE Press, 2005.
7. D. Ashlock and T. von Konigslow. Evolution of artificial ring species. In Proceedings of 2008 World Congress on Computational Intelligence, pages 653-659, 2008.
8. D. Ashlock and E. Warner. The geometry of tartarus fitness cases. In Proceedings of the 2008 Congress on Evolutionary Computation, pages 1309-1316, 2008.
9. W. Ashlock. Using very small population sizes in genetic programming. In Proceedings of the 2006 Congress on Evolutionary Computation, pages 319-326, 2006.
10. W. Ashlock and D. Ashlock. Virtual retroviruses in grid walkers: effects on genome organization. In IEEE Congress on Evolutionary Computation, pages 1-8, 2010.
11. W. Ashlock and D. Ashlock. Designing artificial organisms for use in biological simulations. In IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pages 1-8, 2011.
12. J. J. Freeman. A linear representation for gp using context free grammars. In Genetic Programming 98, proceedings of the third annual genetic programming conference., pages 72-77, San Francisco, 1998. Morgan Kaufmann.
13. D. E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Publishing Company, Inc., Reading, MA, 1989.
14. P. F. Hingston, L. C. Barone, and Z. Michalewicz. Design by Evolution. Springer, New York, 2008.
15. John H Holland. Adaption in Natural and Artificial Systems. The MIT Press, Cambridge, MA, 1992.
16. V. Honovar and K. Balakrishnan. On sensor evolution in robotics. In GP 96, pages 455-460. MIT Press, 1996.
17. J. R. Koza. Genetic Programming. The MIT Press, Cambridge, MA, 1992.
18. J. Krebs, E. S. Goldstein, and S. T. Kilpatrick. Genes X. Jones and Bartlett, Sudbury, MA, 2011.
19. K. Lindgren. Evolutionary phenomena in simple dynamics. In D. Farmer, C. Langton, S. Rasmussen, and C. Taylor, editors, Artificial Life II, pages 1-18. Addison-Wesley, 1991.
20. S. Liu and H. Iba. Plasticity in baldwinian learning. Journal of Advanced Computational Intelligence and Intelligent Informatics, 15(9):1300-1309, 2011.
21. S. Luke, S. Hamahashi, and H. Kitano. "Genetic" programming. In W. Banzhaf et al, editor, Proceedings of the 1999 Genetic and Evolutionary Computation Conference, San Fransisco, 1999. Morgan Kaufmann.
22. G. Syswerda. A study of reproduction in generational and steady state genetic algorithms. In Foundations of Genetic Algorithms, pages 94-101. Morgan Kaufmann, 1991.
23. Astro Teller. The evolution of mental models. In Kenneth Kinnear, editor, Advances in Genetic Programming, chapter 9. The MIT Press, 1994.