Coevolution and Tartarus

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

@InProceedings{Ashlock:2004:CaT,

• title = "Coevolution and Tartarus",
• author = "Daniel Ashlock and Stephen Willson and Nicole Leahy",
• pages = "1618--1624",
• booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
• year = "2004",
• publisher = "IEEE Press",
• month = "20-23 " # jun,
• address = "Portland, Oregon",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Coevolution \& collective behavior, Evolutionary intelligent agents",
• URL = "http://orion.math.iastate.edu/danwell/eprints/TartarusCE.pdf",
• URL = "http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=01331089",
• DOI = "doi:10.1109/CEC.2004.1331089",
• abstract = "This study applies coevolution to the Tartarus task. If the coevolving test cases are viewed as a form of parasite the question of virulence becomes an important feature of the algorithm. This study compares two types of parasites. The impact of coevolution in this study is at odds with intuition and statistically significant. Analysis suggests that disruptive crossover has a key effect. In the presence of disruptive crossover, coevolution may need to be modified to be effective. The key method of dealing with disruptive crossover is tracking the age of the Tartarus agents. Using only older agents to drive coevolution of test cases substantially enhances the performance of one of the two type of coevolution studied.",
• notes = "GP-automata. Disruptive effect of crossover and mutation important in co-evolution studies. CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Daniel Ashlock Stephen J Willson Nicole P Leahy

Citations