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Large Language Models (LLMs) have been increasingly used in real-world settings, yet their strategic decision-making abilities remain largely unexplored. To fully benefit from the potential of LLMs, it's essential to understand their…

人工智能 · 计算机科学 2024-10-16 Nathan Herr , Fernando Acero , Roberta Raileanu , María Pérez-Ortiz , Zhibin Li

LLMs are increasingly used in applications where they interact with humans and other agents. We propose to use behavioural game theory to study LLM's cooperation and coordination behaviour. We let different LLMs play finitely repeated…

计算与语言 · 计算机科学 2025-05-13 Elif Akata , Lion Schulz , Julian Coda-Forno , Seong Joon Oh , Matthias Bethge , Eric Schulz

This paper investigates the strategic decision-making capabilities of three Large Language Models (LLMs): GPT-3.5, GPT-4, and LLaMa-2, within the framework of game theory. Utilizing four canonical two-player games -- Prisoner's Dilemma,…

计算机科学与博弈论 · 计算机科学 2023-09-13 Nunzio Lorè , Babak Heydari

As Large Language Models (LLMs) are integrated into critical real-world applications, their strategic and logical reasoning abilities are increasingly crucial. This paper evaluates LLMs' reasoning abilities in competitive environments…

Game theory has long served as a foundational tool in cybersecurity to test, predict, and design strategic interactions between attackers and defenders. The recent advent of Large Language Models (LLMs) offers new tools and challenges for…

密码学与安全 · 计算机科学 2026-02-19 Daniele Proverbio , Alessio Buscemi , Alessandro Di Stefano , The Anh Han , German Castignani , Pietro Liò

Game theory, as an analytical tool, is frequently utilized to analyze human behavior in social science research. With the high alignment between the behavior of Large Language Models (LLMs) and humans, a promising research direction is to…

人工智能 · 计算机科学 2023-12-13 Caoyun Fan , Jindou Chen , Yaohui Jin , Hao He

We evaluate Large Language Models (LLMs) in repeated game-theoretic settings to assess whether strategic performance reflects genuine reasoning or reliance on memorized patterns. We consider two canonical games, Prisoner's Dilemma (PD) and…

计算与语言 · 计算机科学 2026-05-25 Dimitrios Georgousis , Maria Lymperaiou , Angeliki Dimitriou , Giorgos Filandrianos , Giorgos Stamou

Large language models (LLMs) are increasingly deployed to support human decision-making. This use of LLMs has concerning implications, especially when their prescriptions affect the welfare of others. To gauge how LLMs make social…

计算机与社会 · 计算机科学 2026-01-16 Saptarshi Pal , Abhishek Mallela , Christian Hilbe , Lenz Pracher , Chiyu Wei , Feng Fu , Santiago Schnell , Martin A Nowak

This paper examines the reasoning capabilities of Large Language Models (LLMs) from a novel perspective, focusing on their ability to operate within formally specified, rule-governed environments. We evaluate four LLMs (Gemini 2.5 Pro and…

人工智能 · 计算机科学 2026-02-24 Maciej Świechowski , Adam Żychowski , Jacek Mańdziuk

Large Language Models (LLMs) harness extensive data from the Internet, storing a broad spectrum of prior knowledge. While LLMs have proven beneficial as decision-making aids, their reliability is hampered by limitations in reasoning,…

人工智能 · 计算机科学 2024-03-12 Hongyi Guo , Zhihan Liu , Yufeng Zhang , Zhaoran Wang

Large language models are increasingly used in strategic decision-making settings, yet evidence shows that, like humans, they often deviate from full rationality. In this study, we compare LLMs and humans using experimental paradigms…

人工智能 · 计算机科学 2025-06-12 Kehan Zheng , Jinfeng Zhou , Hongning Wang

Large language models (LLMs) are increasingly used for tasks that require complex reasoning. Most benchmarks focus on final outcomes but overlook the intermediate reasoning steps - such as planning, revision, and decision making under…

人工智能 · 计算机科学 2025-06-16 Xiaopeng Yuan , Xingjian Zhang , Ke Xu , Yifan Xu , Lijun Yu , Jindong Wang , Yushun Dong , Haohan Wang

Machines driven by large language models (LLMs) have the potential to augment humans across various tasks, a development with profound implications for business settings where effective communication, collaboration, and stakeholder trust…

人机交互 · 计算机科学 2025-07-28 Paweł Niszczota , Tomasz Grzegorczyk , Alexander Pastukhov

Large language models (LLMs) have been extensively used as the backbones for general-purpose agents, and some economics literature suggest that LLMs are capable of playing various types of economics games. Following these works, to overcome…

计算机科学与博弈论 · 计算机科学 2024-01-04 Shangmin Guo , Haoran Bu , Haochuan Wang , Yi Ren , Dianbo Sui , Yuming Shang , Siting Lu

We investigated the capability of the GPT-3.5 large language model (LLM) to operationalize natural language descriptions of cooperative, competitive, altruistic, and self-interested behavior in two social dilemmas: the repeated Prisoners…

计算机科学与博弈论 · 计算机科学 2024-07-02 Steve Phelps , Yvan I. Russell

Strategic reasoning enables agents to cooperate, communicate, and compete with other agents in diverse situations. Existing approaches to solving strategic games rely on extensive training, yielding strategies that do not generalize to new…

人工智能 · 计算机科学 2023-05-31 Kanishk Gandhi , Dorsa Sadigh , Noah D. Goodman

In recent years, large language models (LLMs) have shown significant advancements in natural language processing (NLP), with strong capa-bilities in generation, comprehension, and rea-soning. These models have found applications in…

人工智能 · 计算机科学 2025-04-02 Hui Wang

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…

计算与语言 · 计算机科学 2025-04-01 Chen Feng Tsai , Xiaochen Zhou , Sierra S. Liu , Jing Li , Mo Yu , Hongyuan Mei

Strategic decision-making involves interactive reasoning where agents adapt their choices in response to others, yet existing evaluations of large language models (LLMs) often emphasize Nash Equilibrium (NE) approximation, overlooking the…

人工智能 · 计算机科学 2025-11-04 Jingru Jia , Zehua Yuan , Junhao Pan , Paul E. McNamara , Deming Chen

This paper investigates the rationality of large language models (LLMs) in strategic decision-making contexts, specifically within the framework of game theory. We evaluate several state-of-the-art LLMs across a spectrum of…

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