Cellular Automata is a discrete computational modeling method in which space is divided into a grid of cells, each occupying a finite set of states that evolve over time according to local transition rules based on the states of neighboring cells. In crowd simulation and modeling, this approach matters because it offers a computationally efficient way to capture emergent collective behaviors — such as lane formation, congestion, and evacuation dynamics — from simple local interaction rules without requiring continuous equations of motion. Key variants include floor field models, which introduce static and dynamic potential fields to guide agent movement toward exits, and multi-grid or multi-layer extensions that refine spatial resolution or incorporate heterogeneous agent characteristics.
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