TY - GEN
T1 - Adaptation of plans via annotation verification
AU - Kambhampati, Subbarao
AU - Hendler, James A.
N1 - Publisher Copyright:
© ACM 1988.
PY - 1988/6/1
Y1 - 1988/6/1
N2 - The ability to adapt old plans to new situations is essential for a planning system. A perceived problem with the adaptation methods in traditional memory-based planning approaches has been the need for a strong domain model in addition to a library of past plans. In this paper, we argue that the process of adaptation does not need any domain knowledge outside of that which a generative planner has available. We present an approach to plan reuse in which information relevant to the adaptation process is left in the form of annotations on generated plans. Adaptation of a past plan to a new problem situation is focused by a process of annotation verification, which locates applicability failures and suggests appropriate refitting strategies. The generative planner is then called upon to carry out these refits. We give examples from automated process planning (in computer-aided manufacturing) to show how annotation verification helps in adaptation. These examples also help in showing how adaptive planning can be an efficient and viable alternative to the generative and semi-automated variant planning techniques currently used in process planning.
AB - The ability to adapt old plans to new situations is essential for a planning system. A perceived problem with the adaptation methods in traditional memory-based planning approaches has been the need for a strong domain model in addition to a library of past plans. In this paper, we argue that the process of adaptation does not need any domain knowledge outside of that which a generative planner has available. We present an approach to plan reuse in which information relevant to the adaptation process is left in the form of annotations on generated plans. Adaptation of a past plan to a new problem situation is focused by a process of annotation verification, which locates applicability failures and suggests appropriate refitting strategies. The generative planner is then called upon to carry out these refits. We give examples from automated process planning (in computer-aided manufacturing) to show how annotation verification helps in adaptation. These examples also help in showing how adaptive planning can be an efficient and viable alternative to the generative and semi-automated variant planning techniques currently used in process planning.
UR - http://www.scopus.com/inward/record.url?scp=33846164997&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33846164997&partnerID=8YFLogxK
U2 - 10.1145/51909.51929
DO - 10.1145/51909.51929
M3 - Conference contribution
AN - SCOPUS:33846164997
T3 - Proceedings of the 1st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1988
SP - 164
EP - 170
BT - Proceedings of the 1st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1988
A2 - Ali, Moonis
PB - Association for Computing Machinery, Inc
T2 - 1st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1988
Y2 - 1 June 1988 through 3 June 1988
ER -