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Choreographing Superpowered AI Movement in 'Suicide Squad'


This talk presents an expressive and scalable AI movement stack that realizes diverse AI traversal behaviors in Suicide Squad: Kill The Justice League. A hierarchical multi-modal pathfinding approach operating on hyper-connected navigation data is used to produce effective paths in the complex open world of Metropolis. A novel path-planning approach is introduced between pathfinding and path following to create more varied and nuanced traversal decisions. AI path is annotated and broken down into featured patterns based on agent movement constraints and preference and then solved by an HTN-style planner into traversal plans. An adaptive traversal plan execution layer allows AI agents to carry out the planned traversal with the ability to repair and adjust their actions on the fly.

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