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

Young Seol Lee, Sung-Bae Cho

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

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
Volume6
Issue number2
DOIs
Publication statusPublished - 2011 May 1

Fingerprint

Bayesian networks
Context-aware
Petri nets
Petri Nets
Game
Bayesian Networks
Open Source
Module
Evaluate
Design

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Artificial Intelligence

Cite this

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Context-aware Petri net for dynamic procedural content generation in role-playing game. / Lee, Young Seol; Cho, Sung-Bae.

In: IEEE Computational Intelligence Magazine, Vol. 6, No. 2, 5749447, 01.05.2011, p. 16-25.

Research output: Contribution to journalArticle

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