Evolving Object Oriented Agent Programs in Robocup Domain

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "David Enrique {Suarez Pinzon} and 
                 Julian Yezid {Olarte Ramos} and Sergio Andres {Rojas Galeano}",
  title =        "Evolving Object Oriented Agent Programs in Robocup
  booktitle =    "Genetic and Evolutionary Computation Conference
                 {(GECCO2005)} workshop program",
  year =         "2005",
  month =        "25-29 " # jun,
  editor =       "Franz Rothlauf and Misty Blowers and 
                 J{\"u}rgen Branke and Stefano Cagnoni and Ivan I. Garibay and 
                 Ozlem Garibay and J{\"o}rn Grahl and Gregory Hornby and 
                 Edwin D. {de Jong} and Tim Kovacs and Sanjeev Kumar and 
                 Claudio F. Lima and Xavier Llor{\`a} and 
                 Fernando Lobo and Laurence D. Merkle and Julian Miller and 
                 Jason H. Moore and Michael O'Neill and Martin Pelikan and 
                 Terry P. Riopka and Marylyn D. Ritchie and Kumara Sastry and 
                 Stephen L. Smith and Hal Stringer and 
                 Keiki Takadama and Marc Toussaint and Stephen C. Upton and 
                 Alden H. Wright",
  publisher =    "ACM Press",
  address =      "Washington, D.C., USA",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "407--410",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005wks/papers/0407.pdf",
  abstract =     "We describe the application of object oriented genetic
                 programming to the automatic generation of agents under
                 the Object Oriented Paradigm. To generate the agent
                 programs code, we evolve concurrently the methods that
                 represent the agent-environment interaction. We use
                 like terminals and operations the objects that
                 correspond to the context elements. This study uses the
                 simulation league of the Robot World Cup (Robocup) like
                 a testing environment. The fitness function used
                 evaluates the behavior of agent player in several
                 levels that indicates the learning progress. The
                 experimental results indicate that is possible the
                 agent programs evolution under the Object Oriented
  notes =        "Distributed on CD-ROM at GECCO-2005. ACM

Genetic Programming entries for David Enrique Suarez Julian Yezid Olarte Sergio Andres Rojas