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Containing Behavioral Cascades from Manipulated Claims in LLM-Powered Multi-Robot Systems
Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-wide behavioral cascade, causing unnecessary replanning, increased path costs, congestion, or apparent mission infeasibility. Conditioning on a succ
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