Computational models of emotion, personality, and social relationships for interactions in games

Chowanda, Andry; Blanchfield, Peter; Flintham, Martin; Valstar, Michel

Abstract

We present a novel computational model of emotion, personality and social relationships, implemented and evaluated in an existing commercial game (The Elder Scrolls V: Skyrim). We argue that Non Player Characters (NPCs) with such capabilities will accommodate a new experience in playing games and provide evidence supporting this. Applying the ERiSA Framework [1, 2] to the Skyrim Creation Kit, we designed a simple quest and 2 unique NPCs to interact with. When the ERiSA framework is used, players reported significant changes in their social relationship with the two NPCs compared to the baseline. Most importantly, the results further indicate that the models provide a new experience in playing games. In particular, players report enhanced emotional attachment to the NPCs and appear to forge relationships with the NPCs. Finally, the implemented models result in significant changes in the game engagement and the game immersion score.

Citation

Chowanda, A., Blanchfield, P., Flintham, M., & Valstar, M. (in press). Computational models of emotion, personality, and social relationships for interactions in games.

• Conference Name: 2016 International Conference on Autonomous Agents and Multiagent Systems
• End Date: May 13, 2016
• Acceptance Date: Jan 5, 2016
• Deposit Date: Oct 26, 2016
• Journal: The 2016 International Conference on Autonomous Agents & Multiagent Systems
• Electronic ISSN: 978-1-4503-4239-1
• Peer Reviewed: Not Peer Reviewed
• Series Title: AAMAS '16
• Keywords: computational models, game environment, social interactions, social relationships
• Public URL: https://nottingham-repository.worktribe.com/output/773613
• Publisher URL: http://dl.acm.org/citation.cfm?id=2936924.2937151
• Additional Information: Published in AAMAS '16: Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems. Richland S.C. : International Foundation for Autonomous Agents and Multiagent Systems, c2016. ISBN 978145034239, pp. 1343-1344.