Krzysztof Krawiec


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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 behavioral patterns observed in the evolved strategies. #2009LichockiKrawiecEvoGamesBib

@INPROCEEDINGS { 2009LichockiKrawiecEvoGames,
    AUTHOR = { Paweł Lichocki and Krzysztof Krawiec and Wojciech Jaśkowski },
    TITLE = { Evolving Teams of Cooperating Agents for Real-Time Strategy Game },
    BOOKTITLE = { Applications of Evolutionary Computing },
    YEAR = { 2009 },
    EDITOR = { Mario Giacobini and Anthony Brabazon and Stefano Cagnoni and Gianni A. Di Caro and Anik\'{o} Ek\'{a}rt and Anna Isabel Esparcia-Alc\'{a}zar and Muddassar Farooq and Andreas Fink and Penousal Machado },
    PAGES = { 333--342 },
    PUBLISHER = { Springer },
    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 behavioral patterns observed in the evolved strategies. },
    COMMENT = { ProjectELP },
    ISBN = { 978-3-642-01128-3 },
    LOCATION = { Heidelberg },
}


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