Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation
This research introduces a fault-tolerant system for AI agents to safely delegate work across multiple workers while ensuring resource budgets are never overspent or lost due to failures. It formalizes resource limits as dynamic authorization boundaries using 'quantized resource vectors' and a strict settlement protocol, guaranteeing global ledger conservation even when agents fail or messages are duplicated.