AI RESEARCH
Cascade-Aware Multi-Agent Routing: Spatio-Temporal Sidecars and Geometry-Switching
arXiv CS.LG
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ArXi:2603.17112v1 Announce Type: cross A common architectural pattern in advanced AI reasoning systems is the symbolic graph network: specialized agents or modules connected by delegation edges, routing tasks through a dynamic execution graph. Current schedulers optimize load and fitness but are geometry-blind: they do not model how failures propagate differently in tree-like versus cyclic regimes. In tree-like delegation, a single failure can cascade exponentially; in dense cyclic graphs, failures tend to self-limit.