A GP-based Video Game Player

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Baozhu Jia and Marc Ebner and Christian Schack",
  title =        "A GP-based Video Game Player",
  booktitle =    "GECCO '15: Proceedings of the 2015 Annual Conference
                 on Genetic and Evolutionary Computation",
  year =         "2015",
  editor =       "Sara Silva and Anna I Esparcia-Alcazar and 
                 Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and 
                 Christine Zarges and Luis Correia and Terence Soule and 
                 Mario Giacobini and Ryan Urbanowicz and 
                 Youhei Akimoto and Tobias Glasmachers and 
                 Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and 
                 Marta Soto and Carlos Cotta and Francisco B. Pereira and 
                 Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and 
                 Heike Trautmann and Jean-Baptiste Mouret and 
                 Sebastian Risi and Ernesto Costa and Oliver Schuetze and 
                 Krzysztof Krawiec and Alberto Moraglio and 
                 Julian F. Miller and Pawel Widera and Stefano Cagnoni and 
                 JJ Merelo and Emma Hart and Leonardo Trujillo and 
                 Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and 
                 Carola Doerr",
  isbn13 =       "978-1-4503-3472-3",
  pages =        "1047--1053",
  keywords =     "genetic algorithms, genetic programming",
  month =        "11-15 " # jul,
  organisation = "SIGEVO",
  address =      "Madrid, Spain",
  URL =          "http://doi.acm.org/10.1145/2739480.2754735",
  DOI =          "doi:10.1145/2739480.2754735",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "A general video game player is an an agent that can
                 learn to play different video games with no specific
                 domain knowledge. We are working towards developing a
                 GP-based general video game player. Our system
                 currently extracts game state features from screen
                 grabs. This information is then passed on to the game
                 player. Fitness is computed from data obtained directly
                 from the internals of the game simulator. For this
                 paper, we compare three different types of game state
                 features. These features differ in how they describe
                 the position to the nearest object surrounding the
                 player. We have tested our genetic programming game
                 player system on three games: Space Invaders, Frogger
                 and Missile Command. Our results show that a playing
                 strategy for each game can be found efficiently for all
                 three representations.",
  notes =        "Also known as \cite{2754735} GECCO-2015 A joint
                 meeting of the twenty fourth international conference
                 on genetic algorithms (ICGA-2015) and the twentith
                 annual genetic programming conference (GP-2015)",

Genetic Programming entries for Baozhu Jia Marc Ebner Christian Schack