Utilizing Multi-Agent Modelling to Develope Urban Simulations

Cities are faced with many problems such as urban sprawl, congestion, and segregation. They are constantly changing. The heterogeneous nature of cities, make it difficult to generalize localized problems from that of city-wide problems. Computer modeling is becoming an increasingly important tool when examining how cities operate. Agent-based models allow for testing of different hypotheses and theories for urban changes, thus leading to a greater understanding of how cities work. This paper propose a multi-agents systems/simulation model based on integration among parallel processing, coupling with vector GIS,temporal logic analysis and the integration with the rule engine. The efficiency of our approach is shown through some experimental results, which highlights how different theories can be incorporated into one model and demonstrates how the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behavior.