General Policies, Representations, and Planning Width
نویسندگان
چکیده
It has been observed that in many of the benchmark planning domains, atomic goals can be reached with a simple polynomial exploration procedure, called IW, runs time exponential problem width. Such problems have indeed bounded width: width does not grow number variables and is often no greater than two. Yet, while notion become part state- of-the-art algorithms like BFWS, there still good explanation for why so domains In this work, we address question by relating serialized to ideas generalized planning, where general policies aim solve multiple instances all at once. We show property admit optimal terms features are explicitly or implicitly represented domain encoding. The results extended larger class do optimal. study leads also new simple, meaningful, expressive language specifying serializations form policy sketches which used encoding control knowledge hand learning it from traces. use meaning theoretical illustrated through examples.
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2021
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v35i13.17398