新质生产力视角下多代理行为模拟赋能城市设计全路径分析OACHSSCD

Traditional urban design,relying on static blueprints and experiential judgment,faces challenges in addressing the dynamic transformations and diverse demands of contemporary urban development.This necessitates the introduction of new quality productive forces,characterized by technology-driven approaches,data support,and efficient collaboration,to enable scientific decision-making and digitally intelligent governance.Multi-agent behavior simulation(MABS)captures the dynamic interactions between individuals and their environments and establishes a five-stage optimization framework,comprising data acquisition,interaction mechanism extraction,simulation modeling,dynamic simulation output,and design optimization.This method promotes the integration of research,practice,and education in urban design.At the research level,it reveals the dynamic coupling between space and behavior while expanding application scenarios;at the practical level,it enhances decision-making efficiency through a closed-loop process of"simulation-diagnosis-prediction-verification";and at the educational level,it establishes an evidence-based pedagogical framework integrating"experience+practice+simulation+verification".Overall,by enabling intelligent simulation,comprehensive diagnosis,and precise prediction,MABS facilitates the transformation of urban design from experience-driven to data-driven approaches and from static blueprints to dynamic simulation,providing essential methodological support for the refined and digitally intelligent governance of urban spaces.