Dynamic Limits for Bloat Control: Variations on Size and Depth

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Silva:DLf:gecco2004,

• author = "Sara Silva and Ernesto Costa",
• title = "Dynamic Limits for Bloat Control: Variations on Size and Depth",
• booktitle = "Genetic and Evolutionary Computation -- GECCO-2004, Part II",
• year = "2004",
• editor = "Kalyanmoy Deb and Riccardo Poli and Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and Paul Darwen and Dipankar Dasgupta and Dario Floreano and James Foster and Mark Harman and Owen Holland and Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and Dirk Thierens and Andy Tyrrell",
• series = "Lecture Notes in Computer Science",
• pages = "666--677",
• address = "Seattle, WA, USA",
• publisher_address = "Heidelberg",
• month = "26-30 " # jun,
• organisation = "ISGEC",
• publisher = "Springer-Verlag",
• volume = "3103",
• ISBN = "3-540-22343-6",
• ISSN = "0302-9743",
• URL = "http://cisuc.dei.uc.pt/ecos/dlfile.php?fn=714_pub_31030666.pdf&idp=714",
• DOI = "doi:10.1007/b98645",
• size = "12",
• keywords = "genetic algorithms, genetic programming",
• abstract = "We present two important variations on a recently successful bloat control technique, Dynamic Maximum Tree Depth, intended at further improving the results and extending the idea to non tree-based GP. Dynamic Maximum Tree Depth introduces a dynamic limit on the depth of the trees allowed into the population, initially set with a low value but increased whenever needed to accommodate a new best individual that would otherwise break the limit. The first variation to this idea is the Heavy Dynamic Limit that, unlike the original one, may fall again to a lower value after it has been raised, in case the new best individual allows it. The second variation is the Dynamic Size Limit, where size is the number of nodes, instead and regardless of depth. The variations were tested in two problems, Symbolic Regression and Parity, and the results show that the heavy limit performs generally better than the original technique, but the dynamic limit on size fails in the Parity problem. The possible reasons for success and failure are discussed.",
• notes = "GECCO-2004 A joint meeting of the thirteenth international conference on genetic algorithms (ICGA-2004) and the ninth annual genetic programming conference (GP-2004)",

}

Genetic Programming entries for Sara Silva Ernesto Costa

Citations