Procedural Personas as Critics for Dungeon Generation

  • Antonios LiapisEmail author
  • Christoffer Holmgård
  • Georgios N. Yannakakis
  • Julian Togelius
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9028)


This paper introduces a constrained optimization method which uses procedural personas to evaluate the playability and quality of evolved dungeon levels. Procedural personas represent archetypical player behaviors, and their controllers have been evolved to maximize a specific utility which drives their decisions. A “baseline” persona evaluates whether a level is playable by testing if it can survive in a worst-case scenario of the playthrough. On the other hand, a Monster Killer persona or a Treasure Collector persona evaluates playable levels based on how many monsters it can kill or how many treasures it can collect, respectively. Results show that the implemented two-population genetic algorithm discovers playable levels quickly and reliably, while the different personas affect the layout, difficulty level and tactical depth of the generated dungeons.


Level Feature Artificial Agent Strategy Game Human Player Game Level 
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.



The research was supported, in part, by the FP7 ICT project C2Learn (project no: 318480) and by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Antonios Liapis
    • 1
    Email author
  • Christoffer Holmgård
    • 2
  • Georgios N. Yannakakis
    • 1
    • 2
  • Julian Togelius
    • 2
  1. 1.Institute of Digital GamesUniversity of MaltaMsidaMalta
  2. 2.Center for Computer Games ResearchIT University of CopenhagenCopenhagenDenmark

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