mlsanityData to 7 Oct 2026

ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agents

arXiv 2311.03220 ↗First posted 6 Nov 2023cs.CL cs.AI cs.GTcited by 33

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

This paper introduces Alympics (Olympics for Agents), a systematic simulation framework utilizing Large Language Model (LLM) agents for game theory research. Alympics creates a versatile platform for studying complex game theory problems, bridging the gap between theoretical game theory and empirical investigations by providing a controlled environment for simulating human-like strategic interactions with LLM agents. In our pilot case study, the "Water Allocation Challenge," we explore Alympics through a challenging strategic game focused on the multi-round auction on scarce survival resources. This study demonstrates the framework's ability to qualitatively and quantitatively analyze game determinants, strategies, and outcomes. Additionally, we conduct a comprehensive human assessment and an in-depth evaluation of LLM agents in strategic decision-making scenarios. Our findings not only expand the understanding of LLM agents' proficiency in emulating human strategic behavior but also highlight their potential in advancing game theory knowledge, thereby enriching our understanding of both game theory and empowering further research into strategic decision-making domains with LLM agents. Codes, prompts, and all related resources are available at https://github.com/microsoft/Alympics.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 21 of its 34 references that are in the map. First posted on arXiv 6 Nov 2023.

Builds on

21 of 34 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View3 Oct
  2. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 19

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  4. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  5. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
  6. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  7. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
  8. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,173
  9. 2023Cognitive Architectures for Language Agentscited by 422
  10. 2023Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agentscited by 329
  11. 2023Can Large Language Models Transform Computational Social Science?cited by 245
  12. 2023Exploring Large Language Models for Communication Games: An Empirical Study on Werewolfcited by 238
7 more
  1. 2023TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIscited by 184
  2. 2023SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Taskscited by 166
  3. 2023ExpertPrompting: Instructing Large Language Models to be Distinguished Expertscited by 140
  4. 2023ChatDB: Augmenting LLMs with Databases as Their Symbolic Memorycited by 136
  5. 2023Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiationcited by 94
  6. 2020Game-Theoretic Multiagent Reinforcement Learningcited by 92
  7. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arenacited by 78

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 19; 2026: 7.

33 papers.

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  1. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  2. 2025Agentic Large Language Models, a surveycited by 105
  3. 2024GameBench: Evaluating Strategic Reasoning Abilities of LLM Agentscited by 89
  4. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Userscited by 32
  5. 2024K-Level Reasoning: Establishing Higher Order Beliefs in Large Language Models for Strategic Reasoningcited by 21
  6. 2024Toward LLM-Agent-Based Modeling of Transportation Systems: A Conceptual Frameworkcited by 19
  7. 2025FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theorycited by 13
  8. 2025From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligencecited by 13
  9. 2024Evolution of Social Norms in LLM Agents using Natural Languagecited by 12
  10. 2024Large Model Strategic Thinking, Small Model Efficiency: Transferring Theory of Mind in Large Language Modelscited by 7
  11. 2025Approximating Human Strategic Reasoning with LLM-Enhanced Recursive Reasoners Leveraging Multi-agent Hypergamescited by 7
  12. 2025Evolution of Cooperation in LLM-Agent Societies: A Preliminary Study Using Different Punishment Strategiescited by 6
21 more
  1. 2025Reputation as a Solution to Cooperation Collapse in LLM-based MASscited by 6
  2. 2026Persona Vectors in Games: Measuring and Steering Strategies via Activation Vectorscited by 6
  3. 2026TERMS-Bench: Diagnosing LLM Negotiation Agents Beyond Deal Ratecited by 6
  4. 2024CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMscited by 5
  5. 2025CORE: Measuring Multi-Agent LLM Interaction Quality under Game-Theoretic Pressurescited by 5
  6. 2025Chimera: Harnessing Multi-Agent LLMs for Automatic Insider Threat Simulationcited by 4
  7. 2025Carbon and Silicon, Coexist or Compete? A Survey on Human-AI Interactions in Agent-based Modeling and Simulationcited by 3
  8. 2025The Influence of Human-inspired Agentic Sophistication in LLM-driven Strategic Reasonerscited by 3
  9. 2025MASCA: LLM based-Multi Agents System for Credit Assessmentcited by 3
  10. 2025Strategic Communication and Language Bias in Multi-Agent LLM Coordinationcited by 3
  11. 2026Market-Bench: Benchmarking Large Language Models on Economic and Trade Competitioncited by 3
  12. 2025LLMs for Supply Chain Managementcited by 2
  13. 2025Psychological and behavioural responses in human-agent vs. human-human interactions: a systematic review and meta-analysiscited by 2
  14. 2024Configurable Mirror Descent: Towards a Unification of Decision Makingcited by 1
  15. 2026LLMs for Game Theory: Entropy-Guided In-Context Learning and Adaptive CoT Reasoningcited by 1
  16. 2026Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provablycited by 1
  17. 2026HCAG: Hierarchical Abstraction and Retrieval-Augmented Generation on Theoretical Repositories with LLMscited by 1
  18. 2025Position: Emergent Machina Sapiens Urge Rethinking Multi-Agent Paradigmscited by 0
  19. 2025RLRF: Competitive Search Agent Design via Reinforcement Learning from Ranker Feedbackcited by 0
  20. 2025Agentmandering: A Game-Theoretic Framework for Fair Redistricting via Large Language Model Agentscited by 0
  21. 2026RuleSmith: Multi-Agent LLMs for Automated Game Balancingcited by 0

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