智能体经济学：在 minimal 外部条件下，AI 智能体间能否涌现出自发的经济行为？
AI Agent Economics: Can Autonomous Economic Behavior Emerge among AI Agents under Minimal External Conditions?
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中文总结 AI 辅助
该研究探究在无预设策略的情况下，AI 智能体能否涌现经济关系，通过两阶段框架在 GPT 和 DeepSeek 的六智能体世界验证，发现组织源于可执行权利与资源后果，为智能体机制治理审计提供依据。
中文摘要 AI 辅助
多智能体研究通常将 AI 智能体置于预定义的游戏、市场或角色中，这使得很难区分内生经济组织与从场景中继承的行为。我们提出的问题是，当智能体获得可执行的工作、转移、选举和分配机制，但没有规定的社会或经济策略时，经济关系是否会涌现。我们将智能体经济学定义为生产、分配、消费、交换和制度的系统，这些系统会改变智能体未来的可行行动。我们开发了一个两阶段框架，包括无生产边界测试以及在 GPT 和 DeepSeek 上的 24 个独立的六智能体世界。在没有生产任务的情况下，智能体进行沟通并管理资源供给，但没有实质性的智能体间转移活动。在经过验证的工作和稀缺任务访问的情况下，转移、贷款、访问承诺、投票换访问的交换以及分配策略会涌现。在保持选举界面固定的情况下，可执行的分配权限会增加分化，同时减少失败的分配和长期排斥。当能源变得具有象征意义时，延续支持消失，但对任务访问的竞争仍然存在。这些发现表明，组织遵循可执行的权利和资源后果，而非角色标签或提示语言，并促使对实际约束智能体未来行动的机制进行治理审计。
英文摘要
Multi-agent studies commonly place AI agents in predefined games, markets, or roles, making it difficult to distinguish endogenous economic organization from behavior inherited from the scenario. We ask whether economic relations emerge when agents receive executable mechanisms for work, transfer, elections, and allocation but no prescribed social or economic strategy. We define AI Agent Economics as systems of production, allocation, consumption, exchange, and institutions that alter agents' future feasible actions. We develop a two-stage framework comprising a no-production boundary test and 24 independent six-agent worlds across GPT and DeepSeek. Without productive tasks, agents communicate and govern resource provision but show no substantive inter-agent transfer activity. With verified work and scarce task access, transfers, loans, access promises, vote-for-access exchanges, and allocation strategies emerge. Holding the election interface fixed, executable allocation authority increases differentiation while reducing failed allocation and prolonged exclusion. When energy becomes symbolic, continuation support disappears, yet competition over task access persists. These findings show that organization follows executable rights and resource consequences rather than role labels or prompt language, and motivate governance audits of the mechanisms that actually constrain agents' future actions.
