Evolving Teams of Cooperating Agents for Real-Time Strategy Game

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

  title =        "Evolving Teams of Cooperating Agents for Real-Time
                 Strategy Game",
  author =       "Pawel Lichocki and Krzysztof Krawiec and 
                 Wojciech Jaskowski",
  year =         "2009",
  booktitle =    "EvoGAMES",
  series =       "Lecture Notes in Computer Science",
  editor =       "Mario Giacobini and Anthony Brabazon and 
                 Stefano Cagnoni and Gianni Di Caro and Aniko Ekart and 
                 Anna Esparcia-Alcazar and Muddassar Farooq and 
                 Andreas Fink and Penousal Machado",
  volume =       "5484",
  pages =        "333--342",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, real-time
                 strategy games, artificial intelligence",
  DOI =          "doi:10.1007/978-3-642-01129-0_37",
  bibsource =    "OAI-PMH server at infoscience.epfl.ch",
  language =     "en",
  oai =          "oai:infoscience.epfl.ch:147850",
  abstract =     "We apply gene expression programing to evolve a player
                 for a real-time strategy (RTS) video game. The paper
                 describes the game, evolutionary encoding of strategies
                 and the technical implementation of experimental
                 framework. In the experimental part, we compare two
                 setups that differ with respect to the used approach of
                 task decomposition. One of the setups turns out to be
                 able to evolve an effective strategy, while the other
                 leads to more sophisticated yet inferior solutions. We
                 discuss both the quantitative results and the
                 behavioural patterns observed in the evolved
  affiliation =  "Poznan Supercomputing and Networking Centre Poznan

Genetic Programming entries for Pawel Lichocki Krzysztof Krawiec Wojciech Jaskowski