Memetic crossover for genetic programming: Evolution through imitation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3103, Issue , 2004, Pages 459-470

  Eskridge, Brent E ^a   Hougen, Dean F ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS;

CROSSOVER OPERATOR; CROSSOVER POINTS; DOMINANT FACTOR; EVOLUTIONARY PROCESS; IDEAL SOLUTIONS; INTELLIGENT SEARCH; MINIMIZING THE NUMBER OF; TOTAL COMPUTATION TIME;

GENETIC PROGRAMMING;

EID: 34248676603     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24855-2_57     Document Type: Article

References (15)

1. Nordin, P., Banzhaf, W.: Real time control of a Khepera robot using genetic programming. Cybernetics and Control 26 (1997) 533-561
2. Dawkins, R.: The Selfish Gene. Oxford University Press (1976)
3. Moscato, P.: On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Technical Report C3P 826, California Institute of Technology, Pasadena, CA (1989)
4. Hougen, D.F., Carmer, J., Woehrer, M.: Memetic learning: A novel learning method for multi-robot systems. In: International Workshop on Multi-Robot Systems. (2003) Available at http://www.cs.ou.edu/∼hougen/mrs2003.pdf.
5. Eskridge, B.E., Hougen, D.F.: Imitating success: A memetic crossover operator for genetic programming. To appear in: Proceedings of the Congress on Evolutionary Computation, IEEE (2004)
6. Koza, J.R.: Genetic programming: On the programming of computers by natural selection. MIT Press, Cambridge, Mass. (1992)
7. Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programms. MIT Press, Cambridge, MA (1994)
8. D'haeseleer, P.: Context preserving crossover in genetic programming. In: Proceedings of the 1994 IEEE World Congress on Computational Intelligence. Volume 1., Orlando, Florida, USA, IEEE Press (1994) 256-261
9. Langdon, B.: Genetic Programming and Data Structures. PhD thesis, University College, London (1996)
10. Rosca, J.P., Ballard, D.H.: Discovery of subroutines in genetic programming. In Angeline, P.J., Kinnear, Jr., K.E., eds.: Advances in Genetic Programming 2. MIT Press, Cambridge, MA, USA (1996) 177-202
11. Coello, C.A.C.: A comprehensive survey of evolutionary-based multiobjective optimization techniques. Knowledge and Information Systems 1 (1999) 129-156
12. Langdon, W.B., Poli, R.: Fitness causes bloat. In Chawdhry, P.K., Roy, R., Pan, R.K., eds.: Second On-line World Conference on Soft Computing in Engineering Design and Manufacturing, Springer-Verlag London (1997) 13-22
13. Montana, D.J.: Strongly typed genetic programming. Technical Report #7866, 10 Moulton Street, Cambridge, MA 02138, USA (1993)
14. Moriarty, D.E., Schultz, A.C., Grefenstette, J.J.: Evolutionary algorithms for reinforcement learning. Journal of Artificial Intelligence Research 11 (1999) 241-276
15. Luke, S.: (ECJ 10: A Java-based evolutionary compuation and genetic programming research system) Available at http://cs.gmu.edu/∼eclab/projects/ecj/.