  Many businesses and consumers are extending the capabilities of voice-based
services such as Amazon Alexa, Google Home, Microsoft Cortana, and Apple Siri
to create custom voice experiences (also known as skills). As the number of
these experiences increases, a key problem is the discovery of skills that can
be used to address a user's request. In this paper, we focus on conversational
skill discovery and present a conversational agent which engages in a dialog
with users to help them find the skills that fulfill their needs. To this end,
we start with a rule-based agent and improve it by using reinforcement
learning. In this way, we enable the agent to adapt to different user
attributes and conversational styles as it interacts with users. We evaluate
our approach in a real production setting by deploying the agent to interact
with real users, and show the effectiveness of the conversational agent in
helping users find the skills that serve their request.
