Context-aware Petri net for dynamic procedural content generation in role-playing game

Young Seol Lee, Sung Bae Cho

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


In most cases, the story or plot of popular role-playing games is constructed by professional designers as a main content. However, manual design of game content has a limitation in the quantitative aspect; it requires a large amount of time and effort. As game consumers want more diverse and rich contents, it is not easy to satisfy these needs with manual design, so procedural content generation is actively exploited to automatically generate game contents. In this paper, we propose a quest generation method using Petri net modules. A quest depending on the players involvement or type determined by Bayesian network is generated by Petri net. Never Winter Night is used as a game platform to show the feasibility of the proposed method. In future works, we will collect players playing history and evaluate the performance of Bayesian network inference for a players type. Also, we will apply the proposed method to an open-source platform for a complete automatic quest generation system.

Original languageEnglish
Article number5749447
Pages (from-to)16-25
Number of pages10
JournalIEEE Computational Intelligence Magazine
Issue number2
Publication statusPublished - 2011 May

Bibliographical note

Funding Information:
This research was supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0018948).

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Artificial Intelligence


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