Adapting AI Behaviors To Players in Driver San Francisco: Hinted-Execution Behavior Trees
DOI:
https://doi.org/10.1609/aiide.v8i1.12499Keywords:
BT, HeBT, Behavior Trees, Hinted-execution Behavior Trees, AI, gamesAbstract
The creative nature of games makes trying new ideas desirable, but these changes are sometimes very risky. We need to find ways to minimize risks while we build innovative experiences. Driver San Francisco did this by using Hinted-execution Behavior Trees; this technique allows developers to modify existing AI behaviors dynamically with very low risk, and was used to adapt Driver’s getaway AI to players’ skills.
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Published
2021-06-30
How to Cite
Ocio, S. (2021). Adapting AI Behaviors To Players in Driver San Francisco: Hinted-Execution Behavior Trees. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 8(1), 51-56. https://doi.org/10.1609/aiide.v8i1.12499
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