Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T20:27:51.132Z Has data issue: false hasContentIssue false
  • English
  • Français

On the implications of the virtual storyteller’s point of view

Published online by Cambridge University Press:  01 December 2008

Jesús Ibáñez ,
Ruth Aylett ,
Carlos Delgado-Mata  and
Beatriz Molinuevo
Jesús Ibáñez
Affiliation:
Departamento de Tecnología, Universidad Pompeu Fabra, Barcelona, Spain; e-mail: [email protected]
Ruth Aylett
Affiliation:
School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK; e-mail: [email protected]
Carlos Delgado-Mata
Affiliation:
CINAVI, Universidad Bonaterra, Aguascalientes, Mexico; e-mail: [email protected]
Beatriz Molinuevo
Affiliation:
Departamento de Psiquiatria, Universitat Autònoma de Barcelona, Barcelona, Spain; e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper deals with the implications of showing the storyteller’s perspective when telling stories in virtual environments. The paper proposes an open and reusable architecture for the construction of virtual guides who tell stories about the worlds they inhabit from their own perspective. The system consists of two main components: the structure of a knowledge base to code the narrative knowledge about the worlds and a novel hybrid algorithm for the generation of narratives showing the storyteller’s viewpoint. The complete architecture has been developed. Furthermore, we carried out a study with users in order to both validate the implemented storytelling system and test whether the users consider it significantly better or worse (in terms of several aspects related to believability) adding the virtual guide perspective (as both text and animations showing emotions) to the guide discourse. The interesting results are discussed.

Type
Article
Information
The Knowledge Engineering Review , Volume 23 , Issue 4 , December 2008 , pp. 339 - 367
Copyright
Copyright © Cambridge University Press2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adobbati, R., Marshall, A. N., Scholer, A., Tejada, S., Kaminka, G. A. & Schaffer, S. 2001. Gamebots: a 3D virtual world test-bed for multi-agent research. In Second International Workshop on Infrastructure for Agents, MAS, and Scalable MAS, Montreal, Canada.Google Scholar
Aylett, R. 1999. Narrative in virtual environments—towards emergent narrative. In Narrative Intelligence Symposium, AAAI 1999 Fall Symposium Series.Google Scholar
Aylett, R. & Cavazza, M. 2001. Intelligent Virtual Environments—a State-of-the-Art Report. State of Art Reports, Eurographics.Google Scholar
Aylett, R. & Luck, M. 2000. Applying artificial intelligence to virtual reality: intelligent virtual environments. Applied Artificial Intelligence 14(1), 3–32.Google Scholar
Batagelj, V. & Mrvar, A. 2003. Pajek—analysis and visualization of large networks. In Graph Drawing Software, Mathematics and Visualization, Jünger, M. & Mutzel, P. (eds). Springer-Verlag.Google Scholar
Bates, J. 1994. The role of emotion in believable agents. Communications of the ACM 37(7), 122–125.CrossRefGoogle Scholar
Branigan, E. 1992. Narrative Comprehension and Film. Routledge.Google Scholar
Braun, N. 2002. Automated narration—the path to interactive storytelling. In The 2nd International Workshop on Narrative and Interactive Learning Environments, Edinburgh, Scotland.Google Scholar
Brooks, K. M. 1999. Metalinear Cinematic Narrative: Theory, Process, and Tool. PhD thesis, School of Architecture and Planning, MIT.Google Scholar
Cavazza, M., Charles, F. & Mead, S. J. 2001. Characters in search of an author: AI-based virtual storytelling. In International Conference on Virtual Storytelling, 145–154.Google Scholar
Domike, S., Mateas, M. & Vanouse, P. 2002. The recombinant history apparatus presents: Terminal Time. In Narrative Intelligence, Mateas, M. & Sengers, P. (eds). John Benjamins.Google Scholar
Friedman-Hill, E. 2004. Jess the rule engine for the Java platform. Available at http://herzberg.ca.sandia.gov/jess/Google Scholar
Hoorn, J. F., Konijn, E. A. & van der Veer, G. C. 2003. Virtual reality: do no augment realism, augment relevance. Upgrade 4(1), 18–26.Google Scholar
Ibáñez, J. 2004. An Intelligent Guide for Virtual Environments with Fuzzy Queries and Flexible Management of Stories. PhD thesis, Departamento de Ingenieria de la Informacion y las Comunicaciones, Universidad de Murcia.Google Scholar
Isbister, K. & Doyle, P. 1999. Touring machines: Guide agents for sharing stories about digital places. In Working Notes of the 1999 AAAI Fall Symposium on Narrative Intelligence. http://citeseer.ni.nec.com/285732.htmlGoogle Scholar
Jul, S. & Furnas, G. W. 1997. Navigation in electronic worlds. SIGCHI Bulletin 29(4), 44–49.CrossRefGoogle Scholar
Kaminka, G. A., Veloso, M. M., Schaffer, S., Sollitto, C., Adobbati, R. & Marshall, A. N. 2002. Gamebots: a flexible test bed for multiagent team research. Communications of the ACM 45 (1 Special Issue: Game engines in scientific research), 43–45.Google Scholar
Knott, A., Mellish, C., Oberlander, J. & O’Donnell, M. 1996. Sources of flexibility in dynamic hypertext generation. In Proceedings of the 8th International Workshop on Natural Language Generation, Herstmonceux Castle, UK. http://citeseer.ni.nec.com/knott96sources.htmlGoogle Scholar
Laird, J. E. 2002. Research in human-level AI using computer games. Communications of the ACM 45 (1 Special Issue: Game engines in scientific research).CrossRefGoogle Scholar
Lieberman, H. & Liu, H. 2002. Adaptive linking between text and photos using common sense reasoning. In The 2nd International Conference on Adaptive Hypermedia and Adaptive Web Based Systems, AH2002, Malaga, Spain.CrossRefGoogle Scholar
Lieberman, H., Rosenzweig, E. & Singh, P. 2001. ARIA: an agent for annotating and retrieving images. IEEE Computer, 57–61.CrossRefGoogle Scholar
Likert, R. 1932. A technique for the measurement of attitudes. Archives of Psychology 140, 55.Google Scholar
Liu, H. & Lieberman, H. 2002. Robust photo retrieval using world semantics. In The 3rd International Conference on Language Resources and Evaluation Workshop: Using Semantics for Information Retrieval and Filtering (LREC2002), Las Palmas, Canary Islands, Spain.Google Scholar
Liu, H. & Singh, P. 2002. Makebelieve: using commonsense to generate stories. In Proceedings of the 20th National Conference on Artificial Intelligence (AAAI-02), Student Abstracts, 957–958. Edmonton, Canada.Google Scholar
Louchart, S. & Aylett, R. 2002. Narrative theory and emergent interactive narrative. In The 2nd International Workshop on Narrative and Interactive Learning Environments, Edinburgh, Scotland.Google Scholar
Mateas, M. 1999. An Oz-centric review of interactive drama and believable agents. In AI Today: Recent Trends and Developments, Wooldridge, M. & Veloso, M. (eds). Lecture Notes in AI 1600, 297–328. Springer. First appeared in 1997 as Technical report CMU-CS-97-156. Computer Science Department, Carnegie Mellon University.Google Scholar
Mateas, M. & Stern, A. 2000. Towards integrating plot and character for interactive drama. In Working Notes of the Social Intelligent Agents: The Human in the Loop Symposium. AAAI Fall Symposium Series, AAAI Press. A shorter version of this paper appears in Dautenhahn, K. (ed.), Socially Intelligent Agents: The Human in the Loop. Kluwer, 2002.Google Scholar
Murray, J. 1998. Hamlet on the Holodeck: The Future of Narrative in Cyberspace. MIT Press.Google Scholar
MySQL. 2004. MySQL: The world’s most popular open source database. Available at http://www.mysql.com/Google Scholar
Oberlander, J., O’Donnell, M., Knott, A. & Mellish, C. 1998. Conversation in the museum: experiments in dynamic hypermedia with the intelligent labelling explorer. New Review of Hypermedia and Multimedia 4, 11–32.CrossRefGoogle Scholar
O’Donnell, M., Knott, A., Oberlander, J. & Mellish, C. 2000. Optimising text quality in generation from relational databases. In Proceedings of the 1st International Natural Language Generation Conference, Mitzpe Ramon, Israel.CrossRefGoogle Scholar
Polti, G. 1922. The 36 Dramatic Situations. The Writer, Inc.Google Scholar
Propp, V. 1968. Morphology of the Folktale. University of Texas Press. First edition 1928.Google Scholar
Reitmayr, G., Carroll, S., Reitemeyer, A. & Wagner, M. G. 1999. Deepmatrix—an open technology based virtual environment system. The Visual Computer 15(7/8), 395–412.CrossRefGoogle Scholar
Robertson, J. & Oberlander, J. 2002. Ghostwriter: educational drama and presence in a virtual environment. Journal of Computer Mediated Communication 80(1).Google Scholar
Singh, P. 2002. The public acquisition of commonsense knowledge. In Proceedings of AAAI Spring Symposium on Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, Palo Alto, CA.Google Scholar
Spierling, U., Grasbon, D., Braun, N. & Iurgel, I. 2002. Setting the scene: playing digital director in interactive storytelling and creation. Computers & Graphics 26, 31–44.CrossRefGoogle Scholar
Thompson, S. 1955. Motif Index of Folk Literature. Indiana University Press.Google Scholar
Tozzi, V. 2000. Past reality and multiple interpretations in historical investigation. Studies in Social and Political Thought 2, 41–57.Google Scholar
Wilcoxon, F. 1945. Individual comparisons by ranking methods. Biometrics 1, 80–83.CrossRefGoogle Scholar
Young, R. M. 2001. An overview of the Mimesis architecture: integrating intelligent narrative control into an existing gaming environment. In The Working Notes of the AAAI Spring Symposium on Artificial Intelligence and Interactive Entertainment, Stanford, CA.Google Scholar