A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges
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Abstract (arXiv)
The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry. But despite the surge in interest in this rapidly evolving area, there are scarce systematic reviews on their capabilities and potential in distinct impactful scenarios. This paper endeavours to help bridge this gap, offering a thorough examination of the current landscape of LM usage in regards to complex game playing scenarios and the challenges still open. Here, we seek to systematically review the existing architectures of LM-based Agents (LMAs) for games and summarize their commonalities, challenges, and any other insights. Furthermore, we present our perspective on promising future research avenues for the advancement of LMs in games. We hope to assist researchers in gaining a clear understanding of the field and to generate more interest in this highly impactful research direction. A corresponding resource, continuously updated, can be found in our GitHub repository.
Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 72 of its 91 references that are in the map. First posted on arXiv 15 Mar 2024.
Builds on
72 of 91 references.
References · 72
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- 2023Avalon's Game of Thoughts: Battle Against Deception through Recursive Contemplationcited by 102
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- 2023MarioGPT: Open-Ended Text2Level Generation through Large Language Modelscited by 63
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- 2023Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraftcited by 60
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- 2023Lyfe Agents: Generative agents for low-cost real-time social interactionscited by 49
- 2023LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordinationcited by 48
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- 2023GROOT: Learning to Follow Instructions by Watching Gameplay Videoscited by 42
50 most cited of 72 All 72 (JSON)
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Citing papers per year: 2024: 11; 2025: 8; 2026: 3.
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- 2025Can They Dixit? Yes they Can! Dixit as a Playground for Multimodal Language Model Capabilities22 Oct 2025
- 2025Taking Notes Brings Focus? Towards Multi-Turn Multimodal Dialogue Learning10 Mar 2025
- 2025Are Large Vision Language Models Good Game Players?4 Mar 2025
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- 2024Surveying the MLLM Landscape: A Meta-Review of Current Surveys17 Sep 2024
- 2024VideoGameBunny: Towards vision assistants for video games21 Jul 2024
- 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
- 2024Odyssey: Empowering Minecraft Agents with Open-World Skillscited by 26
- 2024A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarioscited by 23
- 2025Leveraging LLM Agents for Automated Video Game Testingcited by 4
- 2025Memory-Augmented State Machine Prompting: A Novel LLM Agent Framework for Real-Time Strategy Gamescited by 2
- 2025Memory-Augmented State Machine Prompting: A Novel LLM Agent Framework for Real-Time Strategy Games21 Oct 2025
- 2025Leveraging LLM Agents for Automated Video Game Testing26 Sep 2025
- 2025Large Language Model Agent: A Survey on Methodology, Applications and Challenges27 Mar 2025
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- 2024Odyssey: Empowering Minecraft Agents with Open-World Skills22 Jul 2024
- 2026AI for Games in the Foundation Model Eracited by 2
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- 2026Order from Chaos: Physical World Understanding from Glitchy Gameplay Videoscited by 1
- 2024Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Datasetcited by 0
- 2026Order from Chaos: Physical World Understanding from Glitchy Gameplay Videos23 Jan 2026
- 2025Shall We Play a Game? Language Models for Open-ended Wargames21 Sep 2025
- 2024Extract Information from Hybrid Long Documents Leveraging LLMs: A Framework and Dataset28 Dec 2024
- 2024PhysGame: Uncovering Physical Commonsense Violations in Gameplay Videos2 Dec 2024
- 2024StraGo: Harnessing Strategic Guidance for Prompt Optimization11 Oct 2024
- 2024On Large Language Models in National Security Applications3 Jul 2024
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