  There have been several attempts to define a plausible motivation for a
chit-chat dialogue agent that can lead to engaging conversations. In this work,
we explore a new direction where the agent specifically focuses on discovering
information about its interlocutor. We formalize this approach by defining a
quantitative metric. We propose an algorithm for the agent to maximize it. We
validate the idea with human evaluation where our system outperforms various
baselines. We demonstrate that the metric indeed correlates with the human
judgments of engagingness.
