Evolving Teams of Cooperating Agents for Real-Time Strategy Game

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.


Publié dans:
Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing, 333 - 342
Présenté à:
1st European Workshop on Bio-inspired Algorithms in Games (EvoGAMES-2009), Tübingen, Germany, April 15-17, 2009
Année
2009
Publisher:
Berlin, Heidelberg, Springer-Verlag
ISBN:
978-3-642-01128-3
Mots-clefs:
Laboratoires:




 Notice créée le 2010-03-26, modifiée le 2019-03-16

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