Cost-Aware Mixture-of-Experts Coordination for Model Markets
The proposed framework transforms Mixture-of-Experts (MoE) from a model learning technique into a market coordination mechanism. Brokers use gating networks to select and combine heterogeneous experts dynamically for buyer requests. This system optimizes for both high predictive quality and lower execution costs through cost-aware routing and revenue allocation, leading to superior market welfare.