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For some time, simulation has been used for policy experimentation with complex urbanregional systems. However, serious difficulties exist in faithfully modeling such systems across scales. Fundamentally new simulation architectures may be required to address conventional policy, for which cross-scale complexities present a challenge. We introduce a new modeling approach for modeling urban-regional systems from the bottom-up and the top-down, using polyspatial computational agents that aredoi:10.1111/j.1757-7802.2012.01084.x fatcat:okbkxn7q3nc2dljbinljikpjgq