Competition Announcement

15 May 2016

We are proud to announce the 1st Text-Based Adventure AI Competition will be taking place at the 2016 IEEE Conference on Computational Intelligence and Games in Santorini, Greece.

Before the widespread availability of graphics displays, text adventure games such as Colossal Cave, Adventure and Zork were popular in the role-playing gaming community. Due to the richness in text adventure games, such games offer a useful testbed for AI research. Building a fully autonomous agent for an arbitrary text-adventure game is AI complete. However, we plan to provide a graded series of test cases, allowing competitors to gradually increase the sophistication of their approach to handle increasingly complex games.

One of the most challenging problems in AI is still that of automatic model acquisition. In 1959, Newell and Simon’s famous `General Problem Solver’ (GPS) famously solved a variety of planning problems such as “The Monkey and Bananas” and “Tower of Hanoi”. However, the domain had to be entirely operationalized beforehand by researchers, leaving GPS only the task of finding the appropriate actions. Of much greater importance is therefore the questions of “how can an agent automatically acquire the necessary knowledge to successfully solve a simple domain?”. We believe that our test bed is appropriate to build towards such an agent and it may also shed light on the relative merits of model-based and model-free approaches.

The competition will be scored according to two independent criteria:

• C1: Score on an unseen game instance (objective, built-in to the instance)
• C2: Freedom from a priori bias (subjective decision by the judges)

C1 is the dominant criterion, with C2 deciding in the event of a tie. C2 is intended to motivate participants to favour agents that have no (or less) prior knowledge of the problem domain built in.

The deadline for the submission of agents is August 31st 2016 23:59 UTC-12. Further deatils on how to submit will be announced here closer to the deadline.

To get started please visit the Github repo and join the conversation in our Google Group mailing list.