---
格式版本: 2
标题: "Evaluating Rational Contracting in Natural Language"
原文链接: "https://arxiv.org/abs/2608.10475"
发布日期: "2026-08-11"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "rule:local:strict_original_body"
发布时间证据: "**\\[v1\\]** Tue, 11 Aug 2026 04:44:50 UTC (2,311 KB)"
发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body"
发布时间校准置信度: "high"
发布时间候选数量: 18
发布时间严格候选数量: 6
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-12T11:31:12+08:00"
发布时间仲裁状态: "skipped"
发布时间仲裁尝试次数: 0
发布时间仲裁耗时毫秒: 0
发现时间: "2026-08-12T11:26:18+08:00"
入库时间: "2026-08-12T03:31:13.021Z"
来源平台: "arXiv 学术论文搜索"
搜索渠道: "source_template"
搜索词: "https://arxiv.org/search/?query=AI&searchtype=all"
匹配关键词:
  - "AI"
相关厂家:
  []
相关专家:
  []
内容类型: "网页"
抓取工具: "Free Fetch + Defuddle"
清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 0
AI分档: "非优质"
AI质检状态: "不通过"
AI打分理由: "论文研究AI agent的合同谈判，不涉及超节点/AI Rack/机柜级AI基础设施及相关技术或商业信息，与项目关注范围完全无关。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-12T11:31:26+08:00"
AI主题相关性: 0
AI来源权威性: 0
AI新颖性: 0
AI技术细节: 0
AI商业部署信号: 0
AI完整性: 0
采集批次: "2026年8月12日2点04分20秒"
采集批次ID: "20260812-020420-289"
去重键: "https://arxiv.org/abs/2608.10475"
---

## Computer Science > Artificial Intelligence

## Title:Evaluating Rational Contracting in Natural Language

[View PDF](https://arxiv.org/pdf/2608.10475) [HTML (experimental)](https://arxiv.org/html/2608.10475v1)

> Abstract:The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols, such agents can be used to negotiate and execute agreements in open-ended natural language. However, most evaluations of these abilities have focused on one-off exchanges or simple economic games, leaving open the rich space of time-extended, contingent, and incomplete contracts made expressible by language; they also focus on raw profit, without measuring the qualities required for trustworthy contracting. We address this by formulating a rational framework for how agents should negotiate and perform natural language contracts in uncertain multi-step environments. Within this framework, we develop metrics and baselines for quantifying rational and cooperative play. To evaluate how agents perform at such contracting, we instantiate our framework in ContractSim, an evaluation suite where two players negotiate and execute a multi-turn supplier contract under environmental and inter-player uncertainty. Across six environments and three supplier settings (catering, hotel cleaning, and AI hosting) we find that current LLM-based agents reach agreement reliably, and negotiate efficient contracts when environmental uncertainty is low. However, under high uncertainty, they often fail to negotiate satisfiable, efficient, or mutually beneficial contracts. They are also frequently uncooperative when executing contracts, violating contract terms for additional profit even when contracts are easy to satisfy. These findings highlight room for improvement in the design of language agents that can negotiate, interpret, and execute contracts both rationally and cooperatively.

| Comments: |  |
| --- | --- |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Science and Game Theory (cs.GT) |
| Cite as: | [arXiv:2608.10475](https://arxiv.org/abs/2608.10475) \[cs.AI\] |
|  | (or [arXiv:2608.10475v1](https://arxiv.org/abs/2608.10475v1) \[cs.AI\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10475](https://doi.org/10.48550/arXiv.2608.10475) |

## Submission history

From: Tan Zhi-Xuan \[[view email](https://arxiv.org/show-email/b19307ed/2608.10475)\]  
**\[v1\]** Tue, 11 Aug 2026 04:44:50 UTC (2,311 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10475) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
