Multi-Agent Data Science Platforms for Real-Time Crisis Management and Forecasting
Keywords:
Multi-Agent Systems, Crisis Management, Real-Time Analytics, Predictive Forecasting, Intelligent Agents, Distributed AIAbstract
Crisis scenarios such as pandemics, natural disasters, and large-scale cyber incidents demand fast, coordinated, and data-driven responses. This paper presents a multi-agent data science platform designed for real-time crisis management and predictive forecasting. The architecture integrates autonomous agents specialized in data ingestion, analytics, simulation, and coordination, enabling collaborative decision-making across domains. Each agent utilizes domain-specific AI models and communicates through a shared knowledge base, ensuring adaptive and resilient responses under uncertain conditions. Evaluation in simulated disaster scenarios demonstrates enhanced response time, prediction accuracy, and operational flexibility compared to centralized systems.
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