Skip to content
RL-KLM implementation that can be used to estimate task completion times for user interface.
Python Shell
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
case1_remote_controller
case2_multimodal
case3_form_filling
demo
optimization
.gitignore
LICENSE
README.md

README.md

KLM modeling with Reinforcement Learning

RL-KLM automates KLM modeling with Reinforcement Learning for User Interface evaluation. KLM models are suited to evaluate point-and-click type of the user interfaces. In our approach Reinforcement Learning agent learns task policies which minimize the task completion time. The learned task policies are then used to form a KLM model to estimate the total task completion time for the user interface.

The currect version of the code assumes that the user interface can be modeled with Finite State Machine (FSM). RL-KLM can learn a policy for a task when the initial and goal states are defined. With FSM, it is possible to generate the tasks automatically.

This repository includes documented codes for all experiments in the paper "RL-KLM: Automating Keystroke-level Modeling with Reinforcement Learning" url: http://doi.org/10.1145/3301275.3302285.

RL-KLM demo evaluates form templates and is located in demo directory. Please read README.md in the demo directory for more details.

Requirements

Codes

  • Demo for form evaluation.
  • Case 1: Computing the average KLM estimate for tactile remote controller with alternative commands.
  • Case2: Computing the average KLM estimate for a multimodal smart alarm and reporting which modalities were used.
  • Case3: Computing KLM for a form and reporting the best path between form items.
  • Optimization: Optimizing simple remote controller.

See README files in each directory for more information.

Coming in Fall 2019.

  • Optimization README
  • Updating to Python3

Contact: Katri Leino ( katri.k.leino a aalto.fi )

You can’t perform that action at this time.