TY - GEN
T1 - HTN plan repair via model transformation
AU - Höller, Daniel
AU - Bercher, Pascal
AU - Behnke, Gregor
AU - Biundo, Susanne
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - To make planning feasible, planning models abstract from many details of the modeled system. When executing plans in the actual system, the model might be inaccurate in a critical point, and plan execution may fail. There are two options to handle this case: the previous solution can be modified to address the failure (plan repair), or the planning process can be re-started from the new situation (re-planning). In HTN planning, discarding the plan and generating a new one from the novel situation is not easily possible, because the HTN solution criteria make it necessary to take already executed actions into account. Therefore all approaches to repair plans in the literature are based on specialized algorithms. In this paper, we discuss the problem in detail and introduce a novel approach that makes it possible to use unchanged, off-the-shelf HTN planning systems to repair broken HTN plans. That way, no specialized solvers are needed.
AB - To make planning feasible, planning models abstract from many details of the modeled system. When executing plans in the actual system, the model might be inaccurate in a critical point, and plan execution may fail. There are two options to handle this case: the previous solution can be modified to address the failure (plan repair), or the planning process can be re-started from the new situation (re-planning). In HTN planning, discarding the plan and generating a new one from the novel situation is not easily possible, because the HTN solution criteria make it necessary to take already executed actions into account. Therefore all approaches to repair plans in the literature are based on specialized algorithms. In this paper, we discuss the problem in detail and introduce a novel approach that makes it possible to use unchanged, off-the-shelf HTN planning systems to repair broken HTN plans. That way, no specialized solvers are needed.
KW - HTN Planning
KW - Plan repair
KW - Re-planning
UR - http://www.scopus.com/inward/record.url?scp=85091145262&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-58285-2_7
DO - 10.1007/978-3-030-58285-2_7
M3 - Conference contribution
AN - SCOPUS:85091145262
SN - 9783030582845
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 88
EP - 101
BT - KI 2020
A2 - Schmid, Ute
A2 - Wolter, Diedrich
A2 - Klügl, Franziska
PB - Springer Science and Business Media Deutschland GmbH
T2 - 43rd German Conference on Artificial Intelligence, KI 2020
Y2 - 21 September 2020 through 25 September 2020
ER -