Can LLMs Play Ô Ăn Quan Game? A Study of Multi-Step Planning and Decision Making
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arXiv
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| Format: | Preprint |
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2025
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| author | Nguyen, Sang Quang Van Nguyen, Kiet Nguyen, Vinh-Tiep Ngo, Thanh Duc Nguyen, Ngan Luu-Thuy Le, Duy-Dinh |
| author_facet | Nguyen, Sang Quang Van Nguyen, Kiet Nguyen, Vinh-Tiep Ngo, Thanh Duc Nguyen, Ngan Luu-Thuy Le, Duy-Dinh |
| contents | In this paper, we explore the ability of large language models (LLMs) to plan and make decisions through the lens of the traditional Vietnamese board game, Ô Ăn Quan. This game, which involves a series of strategic token movements and captures, offers a unique environment for evaluating the decision-making and strategic capabilities of LLMs. Specifically, we develop various agent personas, ranging from aggressive to defensive, and employ the Ô Ăn Quan game as a testbed for assessing LLM performance across different strategies. Through experimentation with models like Llama-3.2-3B-Instruct, Llama-3.1-8B-Instruct, and Llama-3.3-70B-Instruct, we aim to understand how these models execute strategic decision-making, plan moves, and manage dynamic game states. The results will offer insights into the strengths and weaknesses of LLMs in terms of reasoning and strategy, contributing to a deeper understanding of their general capabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_03711 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Can LLMs Play Ô Ăn Quan Game? A Study of Multi-Step Planning and Decision Making Nguyen, Sang Quang Van Nguyen, Kiet Nguyen, Vinh-Tiep Ngo, Thanh Duc Nguyen, Ngan Luu-Thuy Le, Duy-Dinh Computation and Language In this paper, we explore the ability of large language models (LLMs) to plan and make decisions through the lens of the traditional Vietnamese board game, Ô Ăn Quan. This game, which involves a series of strategic token movements and captures, offers a unique environment for evaluating the decision-making and strategic capabilities of LLMs. Specifically, we develop various agent personas, ranging from aggressive to defensive, and employ the Ô Ăn Quan game as a testbed for assessing LLM performance across different strategies. Through experimentation with models like Llama-3.2-3B-Instruct, Llama-3.1-8B-Instruct, and Llama-3.3-70B-Instruct, we aim to understand how these models execute strategic decision-making, plan moves, and manage dynamic game states. The results will offer insights into the strengths and weaknesses of LLMs in terms of reasoning and strategy, contributing to a deeper understanding of their general capabilities. |
| title | Can LLMs Play Ô Ăn Quan Game? A Study of Multi-Step Planning and Decision Making |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2507.03711 |