Multi-Agent Systems for Collaborative Urban Planning Simulation

Multi-Agent Systems (MAS) involve multiple autonomous AI 'agents' interacting within a simulated environment, each with its own goals, rules, and decision-making processes. For urban planning, these agents could represent developers, municipalities, individual homeowners, or even economic factors. By simulating their interactions, MAS can predict the emergent effects of zoning changes, infrastructure projects, tax incentives, or new developments on property values, traffic congestion, and community dynamics, revealing unintended consequences or optimal strategies before physical implementation.