Abstract
Level of detail is a method that involves optimizing the amount of detail that is simulated for some entity. We introduce an event generation method to optimize the level of detail of upcoming events in a simulation. Our method implements a cognitive model, which uses an estimate of the player’s knowledge to estimate their interest in different aspects of the world. Our method predicts the salience of upcoming events, and uses this salience value to define the level of detail of potential new events. An evaluation of our method’s predictive capacity shows generally higher accuracy than a baseline predictor.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cardona-Rivera, R.E., Cassell, B.A., Ware, S.G., Young, R.M.: Indexter: a computational model of the event-indexing situation model for characterizing narratives. In: Proceedings of the 3rd Workshop on Computational Models of Narrative, pp. 34–43 (2012)
Compton, K., Mateas, M.: Casual creators. In: Proceedings of the International Conference on Computational Creativity, ICCC (2015)
Cournoyer, F., Fortier, A.: Massive crowd on assassin’s creed unity: AI recycling. In: Presentation at the Game Developer’s Conference (GDC 2015). GDC Vault, UBM Tech. (2015)
Flores, L.: Level of detail event generation. M.Sc. dissertation. School of Computer Science, Reykjavik University (2017)
Magerko, B.: Evaluating preemptive story direction in the interactive drama architecture. J. Game Dev. 2(3), 25–52 (2007)
Mihalcea, R., Tarau, P.: Textrank: bringing order into texts. In: Conference on Empirical Methods in Natural Language Processing, pp. 404–411. Association for Computational Linguistics (2004)
Paris, S., Gerdelan, A., O’Sullivan, C.: CA-LOD: collision avoidance level of detail for scalable, controllable crowds. In: Egges, A., Geraerts, R., Overmars, M. (eds.) MIG 2009. LNCS, vol. 5884, pp. 13–28. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-10347-6_2
Roth, M., Ben-David, A., Deutscher, D., Flysher, G., Horn, I., Leichtberg, A., Leiser, N., Matias, Y., Merom, R.: Suggesting friends using the implicit social graph. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 233–242. ACM (2010)
Rowe, J.P., Lester, J.C.: Modeling user knowledge with dynamic Bayesian networks in interactive narrative environments. In: 6th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, pp. 57–62. AAAI Press (2010)
Sunshine-Hill, B.: Perceptually driven simulation. Ph.D. thesis, University of Pennsylvania (2011)
Sunshine-Hill, B.: Managing simulation level-of-detail with the LOD trader. In: 6th International Conference on Motion in Games, pp. 13–18. ACM (2013)
Zwaan, R.A., Langston, M.C., Graesser, A.C.: The construction of situation models in narrative comprehension: an event-indexing model. Psychol. Sci. 6(5), 292–297 (1995). JSTOR
Zwaan, R.A., Radvansky, G.A.: Situation models in language comprehension and memory. Psychol. Bull. 123(2), 162–185 (1998). APA
Acknowledgements
Some parts of this text appear in the first author’s M.Sc. dissertation [4].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Flores, L., Thue, D. (2017). Level of Detail Event Generation. In: Nunes, N., Oakley, I., Nisi, V. (eds) Interactive Storytelling. ICIDS 2017. Lecture Notes in Computer Science(), vol 10690. Springer, Cham. https://doi.org/10.1007/978-3-319-71027-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-71027-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-71026-6
Online ISBN: 978-3-319-71027-3
eBook Packages: Computer ScienceComputer Science (R0)