Markets, Not Planners: Decentralized Orchestration of LLM Agents with Private Information
As LLM agents proliferate, built by different parties and with different capabilities and costs, orchestrating them is more like assembling labor across the economy than a computer calling a subroutine. Existing orchestration is typically centralized, with a single planner assigning every task, but this creates a bottleneck as agent pools grow, requires private information (e.g., agents' execution costs), and can easily be manipulated, such that a single inserted preference nearly doubles a favored agent's task share under a centralized LLM allocator. We introduce AgentLance, a repeated labor market in which agents bid on tasks using their private costs and self-maintained strategy notes,...
| Authors | Xiao Liu, Haoyang Li, Songwei Li et al. |
|---|---|
| Primary category | cs.MA |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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