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Using behaviour patterns to generate scripts for computer role-playing games

  • Author / Creator
    Cutumisu, Maria
  • Character behaviours in computer role-playing games have a significant impact on
    game-play, but are often difficult for story authors to implement and modify. Many
    computer games use custom scripts to control the behaviours of non-player characters
    (NPCs). Therefore, a story author must write fragments of computer code
    for the hundreds or thousands of NPCs in the game world. The challenge is to create
    non-repetitive (more entertaining) behaviours for the NPCs without investing
    substantial programming effort to write custom non-trivial scripts for each NPC.
    Consequently, current computer games mostly rely on simplistic non-interactive
    behaviours for NPCs. This research describes the design and implementation of
    a novel behaviour model for interacting NPCs, based on generative design patterns,
    that requires no manual script writing. In this model, NPCs assume different
    roles during the story and select behaviours based on static probabilities or dynamic
    motivations. We also devised a reinforcement learning algorithm, ALeRT, based
    on Sarsa(lambda) and we extended our behaviour model to support behaviour selection
    based on learning. In our model, an NPC can exhibit proactive, reactive, or latent
    behaviours that may be independent or collaborative. This behaviour architecture
    supports behaviours that can be interrupted and resumed based on priorities. The
    implementation of this model produces scripting code for BioWare Corp.'s Neverwinter
    Nights computer role-playing game.

  • Subjects / Keywords
  • Graduation date
    Fall 2009
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R30W2K
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
  • Supervisor / co-supervisor and their department(s)
  • Examining committee members and their departments
    • Schaeffer, Jonathan (Computing Science)
    • Lu, Paul (Computing Science)
    • Carbonaro, Michael (Educational Psychology)
    • Mateas, Michael (Computer Science, University of California, Santa Cruz)