|Spatial Knowledge Representation through Modular Scalable Influence Maps
|Intrinsic Algorithm, LLC
|Track / Format:
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|In game AI, agents require knowledge of what's going on around them and where to "do things". Processing this information in a convenient, efficient way can be challenging. This lecture will show a complete architecture for processing spatial information that enables game agents to understand their place in the world, both for information and behavior execution. This session will show how the architecture is usable for agents in FPS or RPG games, sports games, strategy games, or even for PCG. Lastly, this talk will show how the system can be data-driven to enable designers to craft their own combinations of map info!