Genetic Programming for Layered Learning of Multi-Agent Tasks

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{hsu:2001:gpllmt,

• author = "William H. Hsu and Steven M. Gustafson",
• title = "Genetic Programming for Layered Learning of Multi-Agent Tasks",
• booktitle = "2001 Genetic and Evolutionary Computation Conference Late Breaking Papers",
• year = "2001",
• editor = "Erik D. Goodman",
• pages = "176--182",
• address = "San Francisco, California, USA",
• month = "9-11 " # jul,
• keywords = "genetic algorithms, genetic programming, soccer, RoboCup",
• URL = "http://www.cs.nott.ac.uk/~smg/research/publications/gecco-2001.ps",
• URL = "http://www.cs.nott.ac.uk/~smg/research/publications/gecco-2001.pdf",
• size = "7 pages",
• abstract = "We present an adaptation of the standard genetic program (GP) to hierarchically decomposable, multi-agent learning problems. To break down a problem that requires cooperation of multiple agents, we use the team objective function to derive a simpler, intermediate objective function for pairs of cooperating agents. We apply GP to optimize first for the intermediate, then for the team objective function, using the final population from the earlier GP as the initial seed population for the next. This layered learning approach facilitates the discovery of primitive behaviours that can be reused and adapted towards complex objectives based on a shared team goal. We use this method to evolve agents to play a subproblem of robotic soccer (keep-away soccer). Finally, we show how layered learning GP evolves better agents than standard GP, including GP with automatically defined functions, and how the problem decomposition results in a significant learning-speed increase.",
• notes = "GECCO-2001LB. Luke's ECJ, teambots. See also \cite{gustafson:mastersthesis}",

}

Genetic Programming entries for William H Hsu Steven M Gustafson

Citations