Computer-Supported Form Design using Keystroke-Level Modeling with Reinforcement Learning

Research output: Contribution to conferencePosterScientificpeer-review

Abstract

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
Original languageEnglish
Pages85-86
DOIs
Publication statusPublished - 2019
MoE publication typeNot Eligible
EventInternational Conference on Intelligent User Interfaces - Los Angeles, United States
Duration: 16 Mar 201920 Mar 2019

Conference

ConferenceInternational Conference on Intelligent User Interfaces
Abbreviated titleIUI
CountryUnited States
CityLos Angeles
Period16/03/201920/03/2019

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  • Projects

    COMPUTED: Computational User Interface Design

    Oulasvirta, A., Kim, S., Dayama, N., Shiripour, M., Todi, K., Liao, Y., Koch, J., Nioche, A., Feit, A., Bruckner, L. & Leiva, L.

    27/03/201531/08/2020

    Project: EU: ERC grants

    Cite this

    Leino, K., Todi, K., Oulasvirta, A., & Kurimo, M. (2019). Computer-Supported Form Design using Keystroke-Level Modeling with Reinforcement Learning. 85-86. Poster session presented at International Conference on Intelligent User Interfaces, Los Angeles, United States. https://doi.org/10.1145/3308557.3308704