@InProceedings{Jamakatel2023HTNAviation,
  author     = {Prakash Jamakatel and Pascal Bercher and Axel Schulte and Jane Jean Kiam},
  title      = {Towards Intelligent Companion Systems in General Aviation using Hierarchical Plan and Goal Recognition},
  booktitle  = {Proceedings of the 11th International Conference on Human-Agent Interaction (HAI 2023)},
  year       = {2023},
  publisher  = {Association for Computing Machinery},
  abstract   = {Modern ultralight aircraft in general aviation are equipped with an onboard Pilot Assistance System (PAS) as a companion system, meant to guide the pilot in decision-making, e.g. with plan suggestions, especially in critical situations. For more meaningful guidance, the PAS must possess an accurate and continuous understanding of the context, i.e. the pilot's intention, so that relevant decision-making support is relevant. However, in realistic settings, the pilot's intention is not communicated manually, but can only be proactively monitored by the PAS. This paper explores the possibility of embedding domain expertise using Hierarchical Task Network (HTN) planning to recognise the plan the pilot is currently trying to conduct, by judging from the pilot's actions. Furthermore, by leveraging probability theory for state estimation, since the pilot's actions can only be estimated, we derive belief values to be associated with the recognised plans. Statistical evaluation using data collected from human-in-the-loop tests shows that our intention recognition as plan recognition function is reliable enough to provide the PAS with a contextual understanding. Empirical tests also confirm that our method is efficient enough for real-time implementation.},
  pages      = {229--237},
  doi        = {10.1145/3623809.3623877},
  url_Paper  = {https://bercher.net/publications/2023/Jamakatel2023HTNAviation.pdf},
  keywords   = {conference}
}

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J."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Prakash"],"propositions":[],"lastnames":["Jamakatel"],"suffixes":[]},{"firstnames":["Pascal"],"propositions":[],"lastnames":["Bercher"],"suffixes":[]},{"firstnames":["Axel"],"propositions":[],"lastnames":["Schulte"],"suffixes":[]},{"firstnames":["Jane","Jean"],"propositions":[],"lastnames":["Kiam"],"suffixes":[]}],"title":"Towards Intelligent Companion Systems in General Aviation using Hierarchical Plan and Goal Recognition","booktitle":"Proceedings of the 11th International Conference on Human-Agent Interaction (HAI 2023)","year":"2023","publisher":"Association for Computing Machinery","abstract":"Modern ultralight aircraft in general aviation are equipped with an onboard Pilot Assistance System (PAS) as a companion system, meant to guide the pilot in decision-making, e.g. with plan suggestions, especially in critical situations. For more meaningful guidance, the PAS must possess an accurate and continuous understanding of the context, i.e. the pilot's intention, so that relevant decision-making support is relevant. However, in realistic settings, the pilot's intention is not communicated manually, but can only be proactively monitored by the PAS. This paper explores the possibility of embedding domain expertise using Hierarchical Task Network (HTN) planning to recognise the plan the pilot is currently trying to conduct, by judging from the pilot's actions. Furthermore, by leveraging probability theory for state estimation, since the pilot's actions can only be estimated, we derive belief values to be associated with the recognised plans. Statistical evaluation using data collected from human-in-the-loop tests shows that our intention recognition as plan recognition function is reliable enough to provide the PAS with a contextual understanding. Empirical tests also confirm that our method is efficient enough for real-time implementation.","pages":"229–237","doi":"10.1145/3623809.3623877","url_paper":"https://bercher.net/publications/2023/Jamakatel2023HTNAviation.pdf","keywords":"conference","bibtex":"@InProceedings{Jamakatel2023HTNAviation,\n author = {Prakash Jamakatel and Pascal Bercher and Axel Schulte and Jane Jean Kiam},\n title = {Towards Intelligent Companion Systems in General Aviation using Hierarchical Plan and Goal Recognition},\n booktitle = {Proceedings of the 11th International Conference on Human-Agent Interaction (HAI 2023)},\n year = {2023},\n publisher = {Association for Computing Machinery},\n abstract = {Modern ultralight aircraft in general aviation are equipped with an onboard Pilot Assistance System (PAS) as a companion system, meant to guide the pilot in decision-making, e.g. with plan suggestions, especially in critical situations. For more meaningful guidance, the PAS must possess an accurate and continuous understanding of the context, i.e. the pilot's intention, so that relevant decision-making support is relevant. However, in realistic settings, the pilot's intention is not communicated manually, but can only be proactively monitored by the PAS. This paper explores the possibility of embedding domain expertise using Hierarchical Task Network (HTN) planning to recognise the plan the pilot is currently trying to conduct, by judging from the pilot's actions. Furthermore, by leveraging probability theory for state estimation, since the pilot's actions can only be estimated, we derive belief values to be associated with the recognised plans. Statistical evaluation using data collected from human-in-the-loop tests shows that our intention recognition as plan recognition function is reliable enough to provide the PAS with a contextual understanding. Empirical tests also confirm that our method is efficient enough for real-time implementation.},\n pages = {229--237},\n doi = {10.1145/3623809.3623877},\n url_Paper = {https://bercher.net/publications/2023/Jamakatel2023HTNAviation.pdf},\n keywords = {conference}\n}\n\n","author_short":["Jamakatel, P.","Bercher, P.","Schulte, A.","Kiam, J. 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