Abstract
Swarm intelligence is an emerging subfield of artificial intelligence (AI) where the sophisticated collective intelligence arising from a swarm of simple, unsophisticated individuals cooperating together is used to solve difficult problems. In our opinion, video games can be dramatically improved through swarm intelligence. As an illustration, we introduce a swam intelligence-based system for the representation and animation of some behavioral routines for the AI of the non-player characters (NPCs) of the last-generation first-person shooter video game “Isolated”. In this work we focus on the problems of pathfinding and action planning of the NPCs. Some computer experiments have been conducted to analyze the feasibility and performance of this approach.
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Acknowledgements
This research has been kindly supported by the Computer Science National Program of the Spanish Ministry of Economy and Competitiveness, Project Ref. #TIN2012-30768, Toho University, and the University of Cantabria.
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Díaz, G., Iglesias, A. (2017). Swarm Intelligence Scheme for Pathfinding and Action Planning of Non-player Characters on a Last-Generation Video Game. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_34
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