Research on Intelligent Mechanism of Enterprise Participation in Public Welfare and Social Assistance Tasks Based on QNN-MDRLE

To address inefficiencies in corporate participation in public welfare, this study proposes a Quantum Neural Network-driven Multi-Domain Reinforcement Learning Framework (QNN-MDRLE). The model introduces a Riemannian manifold metric tensor to quantify cultural inertia, transforming social behaviors such as consumer preference and labor discipline into computable constraints. A quantum-classical entanglement optimization mechanism is constructed to collaboratively allocate enterprise capital, material resources, and social worker strategies in Hilbert space. Edge coordinators ensure millisecond-level response for task generation.