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

UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS