Abstract
Pathfinding is a critical element of AI in many modern applications like multiple mobile robots, game industry and flock traffic navigation based on negotiation (FTN). Classical algorithms assume a unique mobile agent with a complete and accurate model of its environment. New applications demand algorithms that consider multiple agents moving in partially known and changing environments. This paper introduces a new algorithm capable of planning paths for multiple agents and takes the FTN scenario as the basis of an example.
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Astengo-Noguez, C., Calzada Gómez, J.R. (2008). Collective Pathfinding in Dynamic Environments. In: Gelbukh, A., Morales, E.F. (eds) MICAI 2008: Advances in Artificial Intelligence. MICAI 2008. Lecture Notes in Computer Science(), vol 5317. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88636-5_81
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DOI: https://doi.org/10.1007/978-3-540-88636-5_81
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