The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete
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arXiv
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| Format: | Preprint |
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2025
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| author | Großmann, Gerrit Ivanova, Larisa Poduru, Sai Leela Tabrizian, Mohaddeseh Mesabah, Islam Selby, David A. Vollmer, Sebastian J. |
| author_facet | Großmann, Gerrit Ivanova, Larisa Poduru, Sai Leela Tabrizian, Mohaddeseh Mesabah, Islam Selby, David A. Vollmer, Sebastian J. |
| contents | According to Yuval Noah Harari, large-scale human cooperation is driven by shared narratives that encode common beliefs and values. This study explores whether such narratives can similarly nudge LLM agents toward collaboration. We use a finitely repeated public goods game in which LLM agents choose either cooperative or egoistic spending strategies. We prime agents with stories highlighting teamwork to different degrees and test how this influences negotiation outcomes. Our experiments explore four questions:(1) How do narratives influence negotiation behavior? (2) What differs when agents share the same story versus different ones? (3) What happens when the agent numbers grow? (4) Are agents resilient against self-serving negotiators? We find that story-based priming significantly affects negotiation strategies and success rates. Common stories improve collaboration, benefiting each agent. By contrast, priming agents with different stories reverses this effect, and those agents primed toward self-interest prevail. We hypothesize that these results carry implications for multi-agent system design and AI alignment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_03961 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete Großmann, Gerrit Ivanova, Larisa Poduru, Sai Leela Tabrizian, Mohaddeseh Mesabah, Islam Selby, David A. Vollmer, Sebastian J. Artificial Intelligence Computation and Language Multiagent Systems I.2.11; I.2.7; I.6; J.4 According to Yuval Noah Harari, large-scale human cooperation is driven by shared narratives that encode common beliefs and values. This study explores whether such narratives can similarly nudge LLM agents toward collaboration. We use a finitely repeated public goods game in which LLM agents choose either cooperative or egoistic spending strategies. We prime agents with stories highlighting teamwork to different degrees and test how this influences negotiation outcomes. Our experiments explore four questions:(1) How do narratives influence negotiation behavior? (2) What differs when agents share the same story versus different ones? (3) What happens when the agent numbers grow? (4) Are agents resilient against self-serving negotiators? We find that story-based priming significantly affects negotiation strategies and success rates. Common stories improve collaboration, benefiting each agent. By contrast, priming agents with different stories reverses this effect, and those agents primed toward self-interest prevail. We hypothesize that these results carry implications for multi-agent system design and AI alignment. |
| title | The Power of Stories: Narrative Priming Shapes How LLM Agents Collaborate and Compete |
| topic | Artificial Intelligence Computation and Language Multiagent Systems I.2.11; I.2.7; I.6; J.4 |
| url | https://arxiv.org/abs/2505.03961 |