A Simulation Model of Intermittently Controlled Point-and-Click Behaviour


We present a novel simulation model of point-and-click behaviour that is applicable both when a target is stationary or moving. To enable more realistic simulation than existing models, the model proposed in this study takes into account key features of the user and the external environment, such as intermittent motor control, click decision-making, visual perception, upper limb kinematics and the effect of input device. The simulated user's point-and-click behaviour is formulated as a Markov decision process (MDP), and the user's policy of action is optimised through deep reinforcement learning. As a result, our model successfully and accurately reproduced the trial completion time, distribution of click endpoints, and cursor trajectories of real users. Through an ablation study, we showed how the simulation results change when the model's sub-modules are individually removed. The implemented model and dataset are publicly available.

Honorable Mention
Seungwon Do
KAIST, DAEJEON, Korea, Republic of
Minsuk Chang
KAIST, Daejeon, Korea, Republic of
Byungjoo Lee
Yonsei University, Seoul, Korea, Republic of





会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Computational Physical Interaction

[A] Paper Room 02, 2021-05-10 17:00:00~2021-05-10 19:00:00 / [B] Paper Room 02, 2021-05-11 01:00:00~2021-05-11 03:00:00 / [C] Paper Room 02, 2021-05-11 09:00:00~2021-05-11 11:00:00
Paper Room 02
12 件の発表
2021-05-10 17:00:00
2021-05-10 19:00:00