- author = "Vic Ciesielski and Dylan Mawhinney",
- title = "Prevention of Early Convergence in Genetic Programming by Replacement of Similar Programs",
- booktitle = "Proceedings of the 2002 Congress on Evolutionary Computation CEC2002",
- editor = "David B. Fogel and Mohamed A. El-Sharkawi and Xin Yao and Garry Greenwood and Hitoshi Iba and Paul Marrow and Mark Shackleton",
- pages = "67--72",
- year = "2002",
- publisher = "IEEE Press",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- organisation = "IEEE Neural Network Council (NNC), Institution of Electrical Engineers (IEE), Evolutionary Programming Society (EPS)",
- ISBN = "0-7803-7278-6",
- month = "12-17 " # may,
-
notes = "CEC 2002 - A joint meeting of the IEEE, the
Evolutionary Programming Society, and the IEE. Held in
connection with the World Congress on Computational
Intelligence (WCCI 2002)
See also \cite{oai:CiteSeerPSU:451316}",
- keywords = "genetic algorithms, genetic programming, CPU time, MAX problem, early convergence prevention, experimental work, fitness function, mutation, mutation rate, premature convergence, randomly generated programs, similar program replacement, similarity matching, soccer playing programs, convergence, programming",
-
DOI = "
doi:10.1109/CEC.2002.1006211",
- abstract = "We have investigated an approach to preventing or minimising the occurrence of premature convergence by measuring the similarity between the programs in the population and replacing the most similar ones with randomly generated programs. On a problem with known premature convergence behaviour, the MAX problem, similarity replacement significantly decreased the rate of premature convergence over the best that could be achieved by manipulation of the mutation rate. The expected CPU time for a successful run was increased due to the additional cost of the similarity matching. On a problem which has a very expensive fitness function, the evolution of a team of soccer playing programs, the degree of premature convergence rate was also significantly reduced. However, in this case the expected time for a successful run was significantly decreased indicating that similarity replacement can be worthwhile for problems with expensive evaluation functions. A significant discovery from our experimental work is that a small change to the way mutation is carried out can result in significant reductions in premature convergence",
