MetaOrch is a deep learning orchestrator that selects optimal agents in multi-agent systems via fuzzy-scored supervision labels, reporting 86.3% accuracy in simulations over random and round-robin baselines.
IEEE/CAA Journal of Automatica Sinica11(4), 1039–1050 (Apr 2024)
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Neural Orchestration for Multi-Agent Systems: A Deep Learning Framework for Optimal Agent Selection in Multi-Domain Task Environments
MetaOrch is a deep learning orchestrator that selects optimal agents in multi-agent systems via fuzzy-scored supervision labels, reporting 86.3% accuracy in simulations over random and round-robin baselines.