  In this paper, we present UbuntuWorld 1.0 LTS - a platform for developing
automated technical support agents in the Ubuntu operating system.
Specifically, we propose to use the Bash terminal as a simulator of the Ubuntu
environment for a learning-based agent and demonstrate the usefulness of
adopting reinforcement learning (RL) techniques for basic problem solving and
troubleshooting in this environment. We provide a plug-and-play interface to
the simulator as a python package where different types of agents can be
plugged in and evaluated, and provide pathways for integrating data from online
support forums like AskUbuntu into an automated agent's learning process.
Finally, we show that the use of this data significantly improves the agent's
learning efficiency. We believe that this platform can be adopted as a
real-world test bed for research on automated technical support.
