The Text-Based Adventure AI Competition

Abstract--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 textbased 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. I. INTRODUCTION Before the widespread availability of graphical displays, text adventures were one of the few game genres that owed their existence solely to computing. The first text adventure was Colossal Cave (also known simply as Adventure), written in 1976 by Will Crowther for the PDP-10 mainframe [1]. With the advent of home computing in the late 1970s, Colossal Cave and other games such as Zork were enjoyed by many. The majority of early text adventures used a narration-action loop that accepted simple commands of the general form VERB or VERB NOUN (e.g. In response to such commands, the programs provided a description of the immediate environment, e.g. 'You are in an open field on the west side of a white house with a boarded front door.