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Permanent link (DOI): https://doi.org/10.7939/R30W2K

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

Descriptions

Other title
Subject/Keyword
computer role-playing games
content generation
reinforcement learning
behaviour patterns
NPC behaviours
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Cutumisu, Maria
Supervisor and department
Szafron, Duane (Computing Science)
Examining committee member and department
Carbonaro, Michael (Educational Psychology)
Schaeffer, Jonathan (Computing Science)
Lu, Paul (Computing Science)
Mateas, Michael (Computer Science, University of California, Santa Cruz)
Department
Department of Computing Science
Specialization

Date accepted
2009-09-01T20:44:14Z
Graduation date
2009-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
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.
Language
English
DOI
doi:10.7939/R30W2K
Rights
License granted by Maria Cutumisu (meric@cs.ualberta.ca) on 2009-08-31T22:15:35Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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