Toward Code Evolution By Artificial Economies

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{baum:1998:tceae,

• author = "Eric B. Baum and Igor Durdanovic",
• title = "Toward Code Evolution By Artificial Economies",
• booktitle = "Late Breaking Papers at the Genetic Programming 1998 Conference",
• year = "1998",
• editor = "John R. Koza",
• pages = "14--22",
• address = "University of Wisconsin, Madison, Wisconsin, USA",
• publisher_address = "Stanford, CA, USA",
• month = "22-25 " # jul,
• publisher = "Stanford University Bookstore",
• keywords = "genetic algorithms, genetic programming",
• URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.7596.pdf",
• size = "9 pages",
• abstract = "We have begun exploring code evolution by artificial economies. We implemented a reinforcement learning machine called Hayek2 consisting of agents, written in a machine language inspired by Ray's Tierra, that interact economically. The economic structure of Hayek2 addresses credit assignment at both the agent and meta levels. Hayek2 succeeds in evolving code to solve Blocks World problems, and has been more effective at this than our hillclimbing program and our genetic program. Our hill climber and our GP also performed well, learning algorithms as strong as a simple search program that incorporates hand-coded domain knowledge. We made efforts to optimise our hillclimbing program and it has features that may be of independent interest. Our genetic program using crossover performed far better than a version using other macro-mutations or our hillclimber, bearing on a controversy in the Genetic Programming literature",
• notes = "citeseerx abstract and PDF not identical GP-98LB. See also \cite{baum:1998:tceaeTR}",

}

Genetic Programming entries for Eric B Baum Igor B Durdanovic

Citations