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arXiv:2304.02868 (cs)
[Submitted on 6 Apr 2023 (v1), last revised 28 Mar 2025 (this
version, v2)]

Title:Can Large Language Models Play Text Games Well? Current
State-of-the-Art and Open Questions

Authors:Chen Feng Tsai, Xiaochen Zhou, Sierra S. Liu, Jing Li, Mo Yu,
Hongyuan Mei
View a PDF of the paper titled Can Large Language Models Play Text
Games Well? Current State-of-the-Art and Open Questions, by Chen Feng
Tsai and Xiaochen Zhou and Sierra S. Liu and Jing Li and Mo Yu and
Hongyuan Mei
View PDF HTML (experimental)

    Abstract:Large language models (LLMs) such as ChatGPT and GPT-4
    have recently demonstrated their remarkable abilities of
    communicating with human users. In this technical report, we take
    an initiative to investigate their capacities of playing text
    games, in which a player has to understand the environment and
    respond to situations by having dialogues with the game world.
    Our experiments show that ChatGPT performs competitively compared
    to all the existing systems but still exhibits a low level of
    intelligence. Precisely, ChatGPT can not construct the world
    model by playing the game or even reading the game manual; it may
    fail to leverage the world knowledge that it already has; it
    cannot infer the goal of each step as the game progresses. Our
    results open up new research questions at the intersection of
    artificial intelligence, machine learning, and natural language
    processing.

Subjects: Computation and Language (cs.CL); Artificial Intelligence
          (cs.AI); Machine Learning (cs.LG)
Cite as:  arXiv:2304.02868 [cs.CL]
          (or arXiv:2304.02868v2 [cs.CL] for this version)
          https://doi.org/10.48550/arXiv.2304.02868
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Mo Yu [view email]
[v1] Thu, 6 Apr 2023 05:01:28 UTC (200 KB)
[v2] Fri, 28 Mar 2025 22:28:31 UTC (219 KB)
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    View a PDF of the paper titled Can Large Language Models Play
    Text Games Well? Current State-of-the-Art and Open Questions, by
    Chen Feng Tsai and Xiaochen Zhou and Sierra S. Liu and Jing Li
    and Mo Yu and Hongyuan Mei
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