The Text-Based Adventure AI Competition
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Aug 2018.
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Citing papers per year: 2021: 4; 2022: 1.
5 papers.
- 2021What Would Jiminy Cricket Do? Towards Agents That Behave Morallycited by 57
- 2021A Systematic Survey of Text Worlds as Embodied Natural Language Environmentscited by 17
- 2021Generalization in Text-based Games via Hierarchical Reinforcement Learningcited by 11
- 2021Playing Codenames with Language Graphs and Word Embeddingscited by 6
- 2022Affordance Extraction with an External Knowledge Database for Text-Based Simulated Environmentscited by 1
- 2022Affordance Extraction with an External Knowledge Database for Text-Based Simulated Environments1 Jul 2022
- 2021What Would Jiminy Cricket Do? Towards Agents That Behave Morally25 Oct 2021
- 2021Generalization in Text-based Games via Hierarchical Reinforcement Learning21 Sep 2021
- 2021A Systematic Survey of Text Worlds as Embodied Natural Language Environments8 Jul 2021
- 2021Playing Codenames with Language Graphs and Word Embeddings12 May 2021