Toward Code Evolution By Artificial Economies (Extended Abstract)

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{oai:CiteSeerPSU:5199,
  author =       "Eric Baum and Igor Durdanovic",
  title =        "Toward Code Evolution By Artificial Economies
                 (Extended Abstract)",
  booktitle =    "Evolution as Computation, DIMACS Workshop, Princeton,
                 January 1999",
  year =         "2001",
  editor =       "Laura F. Landweber and Erik Winfree",
  series =       "Natural Computing Series",
  address =      "Princeton University",
  month =        "11-12 " # jan,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-66709-1",
  URL =          "http://citeseer.ist.psu.edu/5199.html",
  URL =          "http://coblitz.codeen.org:3125/citeseer.ist.psu.edu/cache/papers/cs/2215/http:zSzzSzwww.neci.nj.nec.comzSzhomepageszSzericzSzevpap.pdf/toward-code-evolution-by.pdf",
  size =         "16 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 hillclimber 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 optimize 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 =        "see also \cite{baum:1998:tceaeTR},
                 http://dimacs.rutgers.edu/Workshops/Evolution/

                 Published Jan 2001
                 http://www.amazon.com/exec/obidos/ASIN/3540667091/dominantsystems/107-7663466-9560554",
}

Genetic Programming entries for Eric B Baum Igor Durdanovic

Citations