@inproceedings{0eeb01e807e440aa96727d52a56ca35d,
title = "Detecting AI Planning Modelling Mistakes – Potential Errors and Benchmark Domains",
abstract = "AI planning systems can solve complex problems, leaving domain creation as one of the largest obstacles to a large-scale application of this technology. Domain modeling is a tedious, error-prone and manual process. Unfortunately, domain modelling assistance software is sparse and mostly restricted to editors with only surface-level functionality such as syntax highlighting. We address this important gap by proposing a list of potential domain errors which can be detected by problem parsers and modeling tools. We test well-known planning systems and modeling editors on models with those errors and report their results.",
keywords = "Automated Planning, HDDL Modeling, Knowledge Engineering, Modelling support, PDDL Modeling",
author = "Kayleigh Sleath and Pascal Bercher",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.; 20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023 ; Conference date: 15-11-2023 Through 19-11-2023",
year = "2024",
doi = "10.1007/978-981-99-7022-3\_41",
language = "English",
isbn = "9789819970216",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science+Business Media B.V.",
pages = "448--454",
editor = "Fenrong Liu and Sadanandan, \{Arun Anand\} and Pham, \{Duc Nghia\} and Petrus Mursanto and Dickson Lukose",
booktitle = "PRICAI 2023",
address = "Netherlands",
}