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We introduce a framework for translating game descriptions in natural language into extensive-form representations in game theory, leveraging Large Language Models (LLMs) and in-context learning.
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Extensive Form Games
Jonathan Levin. 2002 · 2024
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Agnieszka Mensfelt, Kostas Stathis, and Vince Trencsenyi. 2024a · 2024
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Autoformalizing and Simulating Game-Theoretic Scenarios using LLM-augmented Agents
Agnieszka Mensfelt, Kostas Stathis, and Vince Trencsenyi. 2024b · 2024
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GPT-4o System Card
OpenAI. 2024 · 2024
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Effect of Private Deliberation: Deception of Large Language Models in Game Play
Kristijan Poje, Mario Brcic, Mihael Kovac, and Marina Bagic Babac. 2024 · 2024
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Gambit: The package for computation in game theory, Version 16.2.0
Rahul Savani and Theodore L. Turocy. 2024 · 2024
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Reflexion: Language Agents with Verbal Reinforcement Learning. In Proceedings of Advances in Neural Information Processing Systems (NeurIPS) . 8634–8652
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2024 · 2024
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Alonso Silva. 2024 · 2024
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From Natural Language to Extensive-Form Game Representations. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems Advances (AAMAS)
Shilong Deng, Yongzhao Wang, and Rahul Savani. 2025 · 2025
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