Abstract
The procedural content of a virtual reality system is a key contributor to its success. However, it is often the case that the content needs to be adjusted. This may take place for a variety of reasons. This research investigates the possibility of the use of machine learning technology to facilitate the modification of a games content. Here, the Deep Dive system was designed originally to predict ancient site locations. Recently it was repurposed to be used as an educational tool to facilitate aspects of STEM education. This required the modification of the content to support this novel use. An evolutionary learning algorithm, Cultural Algorithm, is employed to facilitate the addition of the new content required for the educational application.
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References
Drikx, S., van der Meijer, J., Velden, A., Iosup, A.: Procedural content generation for games. ACM Trans. Multimed. Comput. Commun. Appl. 9(1), 1–22 (2013). https://doi.org/10.1145/2422956.2422957
Amato, A.: Procedural content generation in the game industry. In: Korn, O., Lee, N. (eds.) Game Dynamics, pp. 15–25. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-53088-8_2
Reynolds, R.G., O’Shea, J., Che, Z., Gawasmeh, Y., Meadows, G., Fotouhi, F.: The agile design of reality game AI. In: Multi-agent Applications with Evolutionary Computation and Biologically Inspired Technologies: Intelligent Techniques for Ubiquity and Optimization. IGI Global Press (2011)
Fogarty, J., Reynolds, R.G.,Salamayeh, A., Palazzolo, T.: Serious game modeling of caribou behavior across Lake Huron using cultural algorithms and influence maps. In: O’Shea, J., Sonnenberg, E. (ed.) Archaeological, Ethnographic and Paleo-Environmental Perspectives on Caribou Hunting in the Great Lakes: Maps, Directions and Accommodations, University of Michigan Museum of Anthropology (2015)
Palazzolo, T., Reynolds, R.G., Stanley, S.: Exploring virtual worlds with cultural algorithms: Ancient Alpena-Amberley Land Bridge. In: Cultural Algorithms: Tools for the Engineering of Social Intelligence into Complex Systems, pp. 203–271. IEEE Wiley Press, Hoboken (2020)
O’Shea, J, Lemke, A., Sonnenburg, E., Reynolds, R.G., Abbot, B.: A 9,000 year-old submerged Caribou hunting structure in Lake Huron. In: Proceedings of the National Academy of Science (2014)
Palazzolo, T., Lemke, A., Zhang, C., Saad, S., Reynolds, R.G., O’Shea, J.: DeepDive: the use of virtual worlds to create an ethnography of an ancient civilization. In: Stephanidis, C. et al. (ed.) HCII 2021. LNCS, vol. 13096, pp. 615–629. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-90328-2_42
The IB Learner Profile. https://www.ibo.org/globalassets/publications/recognition/learnerprofile-en.pdf
McLeod, S., Shareski, D.: Different Schools for a Different World. Solution Tree Press, Bloomington (2017)
Culturally Responsive-Sustaining Education Framework. http://www.nysed.gov/crs/framework
Reynolds, R.G.: Culture on the Edge of Chaos: Cultural Algorithms and the Foundations of Social Intelligence, 1st edn. Springer, Switzerland (2018). https://doi.org/10.1007/978-3-319-74171-0
Reynolds, R.G.: Cultural Algorithms: Tools for the Engineering of Social Intelligence into Complex Cultural Systems. Wiley-IEEE Press, Hoboken (2021)
Koenig, S.: Fast replanning for navigation in unknown terrain. IEEE Trans. Rob. 21(3), 354–363 (2005)
Millington, I.: AI for Games. 3rd edn. CRC Press, Boca Raton (2019)
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Saad, S. et al. (2023). Incorporating the Dynamics of Climate Change into the Deep Dive Virtual Reality Underwater Site Prediction System. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2023. Lecture Notes in Computer Science(), vol 14051. Springer, Cham. https://doi.org/10.1007/978-3-031-35894-4_41
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