TY - GEN
T1 - Situated Temporal Planning Using Deadline-aware Metareasoning
AU - Shperberg, Shahaf S.
AU - Coles, Andrew
AU - Karpas, Erez
AU - Ruml, Wheeler
AU - Shimony, Solomon E.
N1 - Publisher Copyright:
Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - We address the problem of situated temporal planning, in which an agent’s plan can depend on scheduled exogenous events, and thus it becomes important to take the passage of time into account during the planning process. Previous work on situated temporal planning has proposed simple pruning strategies, as well as complex schemes for a simplified version of the associated metareasoning problem. Although even the simplified version of the metareasoning problem is NP-hard, we provide a pseudo-polynomial time optimal solution to the case with known deadlines. We leverage intuitions emerging from this case to provide a fast greedy scheme that significantly improves upon previous schemes even for the case of unknown deadlines. Finally, we show how this new method can be applied inside a practical situated temporal planner. An empirical evaluation suggests that the new planner provides state-of-the-art results on problems where external deadlines play a significant role.
AB - We address the problem of situated temporal planning, in which an agent’s plan can depend on scheduled exogenous events, and thus it becomes important to take the passage of time into account during the planning process. Previous work on situated temporal planning has proposed simple pruning strategies, as well as complex schemes for a simplified version of the associated metareasoning problem. Although even the simplified version of the metareasoning problem is NP-hard, we provide a pseudo-polynomial time optimal solution to the case with known deadlines. We leverage intuitions emerging from this case to provide a fast greedy scheme that significantly improves upon previous schemes even for the case of unknown deadlines. Finally, we show how this new method can be applied inside a practical situated temporal planner. An empirical evaluation suggests that the new planner provides state-of-the-art results on problems where external deadlines play a significant role.
UR - http://www.scopus.com/inward/record.url?scp=85124615302&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85124615302
T3 - Proceedings International Conference on Automated Planning and Scheduling, ICAPS
SP - 340
EP - 348
BT - 31st International Conference on Automated Planning and Scheduling, ICAPS 2021
A2 - Biundo, Susanne
A2 - Do, Minh
A2 - Goldman, Robert
A2 - Katz, Michael
A2 - Yang, Qiang
A2 - Zhuo, Hankz Hankui
PB - Association for the Advancement of Artificial Intelligence
T2 - 31st International Conference on Automated Planning and Scheduling, ICAPS 2021
Y2 - 2 August 2021 through 13 August 2021
ER -