Research on the Development of 3D Intelligent Modeling Platform Based on Agent Model

To address the bottlenecks in traditional 3D pipeline embedded iron modeling, such as frequent manual intervention and low efficiency in multi-disciplinary collaboration, this study proposes an intelligent modeling platform architecture based on multi-Agent cooperation. The platform adopts a hierarchical collaborative design, comprising four layers: the user interaction layer (3D visualization and dynamic parameter configuration), the core decision-making layer (task scheduling and conflict coordination), the data layer (structured knowledge base and real-time caching), and the execution layer (specialized Agent cluster), collectively forming a closed-loop autonomous decision-making system. By leveraging knowledge graph technology, the platform encodes design rules and historical cases into structured knowledge, while integrating a dynamic path planning mechanism to enable cross-disciplinary collaborative optimization-for example, automatically adjusting anchoring strategies when civil engineering model accuracy is insufficient. The multi-Agent negotiation mechanism significantly enhances adaptability in complex engineering scenarios. Experimental results demonstrate that the platform can substantially reduce modeling cycles and minimize human errors. This research provides an extensible technical paradigm for intelligent engineering design. Future work will focus on deep integration with digital twin technologies to strengthen full lifecycle management capabilities.