Using context-aware crossover to improve the performance of GP

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{1144146,

• author = "Hammad Majeed and Conor Ryan",
• title = "Using context-aware crossover to improve the performance of {GP}",
• booktitle = "{GECCO 2006:} Proceedings of the 8th annual conference on Genetic and evolutionary computation",
• year = "2006",
• editor = "Maarten Keijzer and Mike Cattolico and Dirk Arnold and Vladan Babovic and Christian Blum and Peter Bosman and Martin V. Butz and Carlos {Coello Coello} and Dipankar Dasgupta and Sevan G. Ficici and James Foster and Arturo Hernandez-Aguirre and Greg Hornby and Hod Lipson and Phil McMinn and Jason Moore and Guenther Raidl and Franz Rothlauf and Conor Ryan and Dirk Thierens",
• volume = "1",
• ISBN = "1-59593-186-4",
• pages = "847--854",
• address = "Seattle, Washington, USA",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2006/docs/p847.pdf",
• DOI = "doi:10.1145/1143997.1144146",
• publisher = "ACM Press",
• publisher_address = "New York, NY, 10286-1405, USA",
• month = "8-12 " # jul,
• organisation = "ACM SIGEVO (formerly ISGEC)",
• keywords = "genetic algorithms, genetic programming, context, context aware crossover, destructive effects, one point crossover, standard crossover, tree context",
• size = "8 pages",
• abstract = "This paper describes the use of a recently introduced crossover operator for GP, context-aware crossover. Given a randomly selected subtree from one parent, context-aware crossover will always find the best location to place the subtree in the other parent.

  We examine the performance of GP when context-aware crossover is used as an extra crossover operator, and show that standard crossover is far more destructive, and that performance is better when only context-aware crossover is used.

  There is still a place for standard crossover, however, and results suggest that using standard crossover in the initial part of the run and then switching to context-aware crossover yields the best performance.

  We show that, across a range of standard GP benchmark problems, context-aware crossover produces a higher best fitness as well as a higher mean fitness, and even manages to solve the 11-bit multiplexer problem without ADFs. Furthermore, the individuals produced this way are much smaller than standard GP, and far fewer individual evaluations are required, so GP achieves a higher fitness by evaluating fewer and smaller individuals.",

• notes = "GECCO-2006 A joint meeting of the fifteenth international conference on genetic algorithms (ICGA-2006) and the eleventh annual genetic programming conference (GP-2006).

  ACM Order Number 910060",

}

Genetic Programming entries for Hammad Majeed Conor Ryan

Citations