Abstract
We adapt a scalable layered intelligence technique from the game industry, for agent-based crowd simulation. We extend this approach for planned movements, pursuance of assignable goals, and avoidance of dynamically introduced obstacles/threats as well as congestions, while keeping the system scalable with the number of agents. We demonstrate the various behaviors in hall-evacuation scenarios, and experimentally establish the scalability of the frame rates with increasing numbers of agents.
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