# 思维经济：通过经济交互涌现的多智能体智能

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-06-01 08:00
- AIHOT 分数：54
- AIHOT 链接：https://aihot.virxact.com/items/cmpzb4mkf01wnslkpr5fh7dx0
- 原文链接：https://arxiv.org/abs/2606.02859

## AI 摘要

受哈耶克市场去中心化协调理论启发，多智能体系统通过拍卖竞争行动权、交换支付并从环境奖励积累财富，经济信号实现去中心化信用分配，驱动无需全局协调的规划。种群通过经济选择演化：高效智能体积累财富并经历利用性变异，低效者破产后被探索性替代。初始为弱智能体的经济系统在数学推理、金融研究、科学研究、加速器设计、分布式系统优化五个任务上涌现多步推理策略，性能超越更强单一模型基线。理论分析揭示经济动力学如何将局部激励与长期全局性能关联。

## 正文

How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedrich Hayek's economic theory of decentralized coordination in markets, we study this question through an agent economy in which agents compete via auctions for the right to act, exchange payments, and accumulate wealth from environmental rewards. These simple economic signals induce decentralized credit assignment, driving planning without global orchestration or explicit communication protocols. The population evolves through economic selection: effective agents accumulate wealth and are mutated via exploitation, while ineffective ones go bankrupt and are replaced via exploration. We show that, initialized with weak agents, the economy produces emergent multi-step reasoning strategies and outperforms stronger monolithic baselines across five agentic tasks, including mathematical reasoning, financial research, scientific research, accelerator design, and distributed-system optimization. We further provide theoretical insights into how economic dynamics shape agent behaviors, linking local incentives to long-term global performance. Our results suggest a new path to multi-agent intelligence: rather than engineering coordination, we can design decentralized incentive structures under which it automatically emerges.