Nested Look-Ahead Evolutionary Algorithm Based Planning for a Believable Diplomacy Bot

  • Markus Kemmerling
  • Niels Ackermann
  • Mike Preuss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6624)


With regard to literature, improved estimations for the number of possible moves and placements are provided, showing that the complexity of Diplomacy is enormous, making it a good candidate for machine learning and evolutionary learning techniques. To enhance the playing strength of an existing Diplomacy bot and alleviate the distance to the presumed best current bot, a look-ahead planning component based on nested evolutionary algorithms, is then implanted into an already existing bot. The experimental investigation shows that the resulting bot is significantly improved.


Multiagent System Board Game Playing Strength Coastal Province Startup Phase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Markus Kemmerling
    • 1
  • Niels Ackermann
    • 2
  • Mike Preuss
    • 2
  1. 1.Robotics Research Institute, Section Information TechnologyTechnische Universität DortmundGermany
  2. 2.Chair of Algorithm Engineering, Computational Intelligence Group, Dept. of Computer ScienceTechnische Universität DortmundGermany

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