  In 2016, 2017, and 2018 at the IEEE Conference on Computational Intelligence
in Games, the authors of this paper ran a competition for agents that can play
classic text-based adventure games. This competition fills a gap in existing
game AI competitions that have typically focussed on traditional card/board
games or modern video games with graphical interfaces. By providing a platform
for evaluating agents in text-based adventures, the competition provides a
novel benchmark for game AI with unique challenges for natural language
understanding and generation. This paper summarises the three competitions ran
in 2016, 2017, and 2018 (including details of open source implementations of
both the competition framework and our competitors) and presents the results of
an improved evaluation of these competitors across 20 games.
