Researchers

Kenny Fung

Master's Student, Unity and Angular Development

Projects

SWaGUR: Saskatchewan-Waterloo Games User Research

Developing and Analysing Adaptive, Enjoyable, and Engaging Human-Computer Interfaces

Publications

Year 2020

LightPlay: An Ambient Light System for Video Game Indicators and Notifications

@mastersthesis{fung2020lightplay,
  title={LightPlay: An Ambient Light System for Video Game Indicators and Notifications},
  author={Fung, Kin Pong},
  year={2020},
  school={University of Waterloo}
}

Video games often have indicators and notifications to convey in-game information. However, displaying these visuals on-screen come with trade-offs, such as consuming screen real estate and an inability for them to be configured independently from its host screen; denying users freedoms such as increasing indicator and notification brightness levels for better awareness without increasing the brightness of main content. As an alternative, we introduce LightPlay, an ambient light system set on the back border of a monitor to display video game indicators and notifications. We compare the speed, error rate, and perceived workload, between on-screen and ambient light indicators and notifications in a first-person camera view video game environment. Results show that ambient lights provide 17.5% faster times for capturing attention compared to on-screen indicators. In addition, ambient lights performed at least as well as on-screen across all other tested metrics.

Year 2019

Biologically-Inspired Gameplay: Movement Algorithms for Artificially Intelligent (AI) Non-Player Characters (NPC)

@inproceedings{Wehbe:2019:10.20380/GI2019.28,
 author = {Wehbe, Rina and Riberio, Giovanni and Fung, Kin and Nacke, Lennart and Lank, Edward},
 title = {Biologically-Inspired Gameplay: Movement Algorithms for Artificially Intelligent (AI) Non-Player Characters (NPC)},
 booktitle = {Proceedings of Graphics Interface 2019},
 series = {GI 2019},
 year = {2019},
 issn = {0713-5424},
 isbn = {978-0-9947868-4-5},
 location = {Kingston, Ontario},
 numpages = {9},
 doi = {10.20380/GI2019.28},
 publisher = {Canadian Information Processing Society},
 keywords = {Games User Research (GUR), Biological Algorithms, Non-player Characters (NPCs), Artifical Intelligence (AI), Movement in Games},
}

In computer games, designers frequently leverage biologicallyinspired movement algorithms such as flocking, particle swarm optimization, and firefly algorithms to give players the perception of intelligent behaviour of groups of enemy non-player characters (NPCs). While extensive effort has been expended designing these algorithms, a comparison between biologically inspired algorithms and naive directional algorithms (travel towards the opponent) has yet to be completed. In this paper, we compare the biological algorithms listed above against a naive control algorithm to assess the effect that these algorithms have on various measures of player experience. The results reveal that the Swarming algorithm, followed closely by Flocking, provide the best gaming experience. However, players noted that the firefly algorithm was most salient. An understanding of the strengths of different behavioural algorithms for NPCs will contribute to the design of algorithms that depict more intelligent crowd behaviour in gaming and computer simulations.