TY - GEN
T1 - On Succinct Groundings of HTN Planning Problems
AU - Behnke, Gregor
AU - Holler, Daniel
AU - Schmid, Alexander
AU - Bercher, Pascal
AU - Biundo, Susanne
N1 - Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020
Y1 - 2020
N2 - Both search-based and translation-based planning systems usually operate on grounded representations of the problem. Planning models, however, are commonly defined using lifted description languages. Thus, planning systems usually generate a grounded representation of the lifted model as a preprocessing step. For HTN planning models, only one method to ground lifted models has been published so far. In this paper we present a new approach for grounding HTN planning problems that produces smaller groundings in a shorter timespan than the previously published method.
AB - Both search-based and translation-based planning systems usually operate on grounded representations of the problem. Planning models, however, are commonly defined using lifted description languages. Thus, planning systems usually generate a grounded representation of the lifted model as a preprocessing step. For HTN planning models, only one method to ground lifted models has been published so far. In this paper we present a new approach for grounding HTN planning problems that produces smaller groundings in a shorter timespan than the previously published method.
UR - http://www.scopus.com/inward/record.url?scp=85098773663&partnerID=8YFLogxK
U2 - 10.1609/aaai.v34i06.6529
DO - 10.1609/aaai.v34i06.6529
M3 - Conference contribution
T3 - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
SP - 9775
EP - 9784
BT - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
PB - AAAI Press
T2 - 34th AAAI Conference on Artificial Intelligence, AAAI 2020
Y2 - 7 February 2020 through 12 February 2020
ER -