Projekteja vuodessa
Abstrakti
The Keystroke-Level Model (KLM) is commonly used to predict a user’s task completion times with graphical user interfaces. With KLM, the user’s behavior is modeled with a linear function of independent, elementary operators. Each task can be completed with a sequence of operators. The policy, or the assumed sequence that the user executes, is typically pre-specified by the analyst. Using Reinforcement Learning (RL), RL-KLM [4] proposes an algorithmic method to obtain this policy automatically. This approach yields user-like policies in simple but realistic interaction tasks, and offers a quick way to obtain an upper bound for user performance. In this demonstration, we show how a policy is automatically learned by RL-KLM in form-filling tasks. A user can interact with the system by placing form fields onto a UI canvas. The system learns the fastest filling order for the form template according to Fitts’ Law operators, and computes estimates the time required to complete the form. Attendees are able to iterate over their designs to see how the changes in designs affect user’s policy and the task completion time.
This demo accompanies an accepted paper at IUI 2019 titled ‘RL-KLM: Automating Keystroke-level Modeling with Reinforcement Learning’.
DOI: http://doi.org/10.1145/3301275.3302285
This demo accompanies an accepted paper at IUI 2019 titled ‘RL-KLM: Automating Keystroke-level Modeling with Reinforcement Learning’.
DOI: http://doi.org/10.1145/3301275.3302285
Alkuperäiskieli | Englanti |
---|---|
Sivut | 85-86 |
DOI - pysyväislinkit | |
Tila | Julkaistu - 2019 |
OKM-julkaisutyyppi | Ei sovellu |
Tapahtuma | International Conference on Intelligent User Interfaces - Los Angeles, Yhdysvallat Kesto: 16 maalisk. 2019 → 20 maalisk. 2019 |
Conference
Conference | International Conference on Intelligent User Interfaces |
---|---|
Lyhennettä | IUI |
Maa/Alue | Yhdysvallat |
Kaupunki | Los Angeles |
Ajanjakso | 16/03/2019 → 20/03/2019 |
Sormenjälki
Sukella tutkimusaiheisiin 'Computer-Supported Form Design using Keystroke-Level Modeling with Reinforcement Learning'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.Projektit
- 1 Päättynyt
-
COMPUTED: Computational User Interface Design
Feit, A. (Projektin jäsen), Oulasvirta, A. (Vastuullinen tutkija), Todi, K. (Projektin jäsen), Dayama, N. (Projektin jäsen), Koch, J. (Projektin jäsen), Nancel, M. (Projektin jäsen), Brückner, L. (Projektin jäsen), Shiripour, M. (Projektin jäsen), Leiva, L. (Projektin jäsen), Kim, S. (Projektin jäsen), Liao, Y.-C. (Projektin jäsen) & Nioche, A. (Projektin jäsen)
27/03/2015 → 31/03/2020
Projekti: EU: ERC grants