When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling
Ziqi Wang, Yuhao Yang, Zhiwei Ling, Wenzhuo Qian, Hailiang Zhao

TL;DR
This paper introduces DESBench, a benchmark for evaluating hierarchical agent coordination in industrial scheduling, revealing trade-offs among different coordination paradigms in complex, dynamic environments.
Contribution
It presents a new benchmark and analysis framework for studying coordination paradigms in multi-agent industrial scheduling environments.
Findings
Centralized coordination is robust and communication-efficient but scales poorly.
Hierarchical coordination improves efficiency but suffers from cross-level misalignment.
Heterarchical coordination is flexible but communication-heavy.
Abstract
Recent advances in agent and multi-agent systems have shown strong performance on tool use, reasoning, and collaborative tasks. However, existing benchmarks mostly evaluate task completion in weakly coupled environments, and provide limited support for studying coordination in shared, dynamically evolving systems with hierarchy and coupled constraints. This leaves an important question underexplored: when do different coordination paradigms succeed or fail? We introduce Distributed Event-driven Scheduling Benchmark (DESBench), a benchmark for evaluating agent coordination in hierarchical event-driven scheduling. Built on a shared discrete-event driven environment in industrial scheduling, our benchmark captures multi-timescale decision making, partial observability, and dynamically coupled constraints. We define tasks and metrics that evaluate effectiveness, constraint alignment,…
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