Evolutionary Solo Pong Players

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

@TechReport{langdon:2005:pongtr,
  author =       "W. B. Langdon and Riccardo Poli",
  title =        "Evolutionary Solo Pong Players",
  institution =  "Department of Computer Science, University of Essex",
  year =         "2005",
  number =       "CSM-423",
  address =      "Colchester, UK",
  month =        "17 " # mar,
  keywords =     "genetic algorithms, genetic programming, XPS, games,
                 AI, PSO",
  URL =          "http://www.cs.essex.ac.uk/technical-reports/2005/csm423.pdf",
  ISSN =         "1744-8050",
  abstract =     "An Internet Java Applet
                 http://www.cs.essex.ac.uk/staff/poli/SoloPong/ allows
                 users anywhere to play the Solo Pong game. We compare
                 people's performance to a hand coded ``Optimal'' player
                 and programs automatically produced by artificial
                 intelligence. The AI techniques are: genetic
                 programming, including a hybrid of GP and a human
                 designed algorithm, and a particle swarm optimiser. The
                 AI approaches are not fine tuned. GP and PSO find good
                 players. Evolutionary computation (EC) is able to beat
                 both human designed code and human players.",
  notes =        "Replaced by langdon:2005:CECa",
  size =         "18 pages",
}

Genetic Programming entries for William B Langdon Riccardo Poli

Citations