Evolutionary Solo Pong Players

Created by W.Langdon from gp-bibliography.bib Revision:1.7642

@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