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MAS-Loop: Beyond One-Shot Orchestration towards Self-Evolving Multi-Agent Systems
Training-time multi-agent system (MAS) design seeks to learn reusable orchestration policies, yet prevailing approaches remain largely one-shot: an Orchestrator generates a system but only observes and learns from its terminal outcome. This paradigm discards execution trajectories that expose system
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