Abstract
We present a general framework for Game Artificial Intelligence Planning (AIP) Analytics. The objective is to provide analytic tools to study and improve AIP components and their use in video-games. Extraction and formatting of AI data is first described and discussed. Then AIP metrics are listed with examples and illustrations from three popular First-Person Shooters: F.E.A.R. (2005), KillZone 3 (2011) and Transformers 3: Fall of Cybertron (2012). The patterns we discovered in our study clearly show the AIP component is called more often by the game over the years.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
2 articles.
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1. Comparing Behaviour Tree and Hierarchical Task Network Planning Methods for their Impact on Player Experience;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05
2. Planning for millions of NPCs in Real-Time;2022 IEEE Symposium Series on Computational Intelligence (SSCI);2022-12-04