multimodal-integration

The paper introduces MACTS-EM, a multi-agent collaborative framework for time series forecasting that uses specialised agents, a meta-cognitive layer, emergent memory, and multimodal integration, reporting 8-12% accuracy gains and improved zero-shot transfer and regime-shift resilience across financial, climate, energy, and pandemic datasets.