Abstract
A hierarchical task planning structure is favorable for its capability to accommodate constraints at different abstraction levels and also for the similarity of its planning approach as a human. This structure is adopted for the task planning for multiple HAPS. However, the combinatorial search problem grows with the presence of multiple agents. This work proposes a method to guide the decomposition of the tasks down the hierarchy with genetic algorithm in order to find quality plans within limited time.
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Kiam, J.J., Hehtke, V., Besada-Portas, E., Schulte, A. (2019). Hierarchical Planning Guided by Genetic Algorithms for Multiple HAPS in a Time-Varying Environment. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration 2019. IHSI 2019. Advances in Intelligent Systems and Computing, vol 903. Springer, Cham. https://doi.org/10.1007/978-3-030-11051-2_109
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DOI: https://doi.org/10.1007/978-3-030-11051-2_109
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