Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Planning. Pages 1620-1625.
Abstract
The search space in partial-order planning grows quickly with the number of subgoals and initial conditions, as well as less countab le factors such as operator ordering and subgoal interactions. For partial-order planners to solve more than simple problems, the expansion of the search space will need to be controlled. This paper presents four new approaches to controlling search space expansion by exploiting commona lities in emerging plans. These approaches are described in terms of their algorithms, their effect on the completeness and correctness of the underlying planner and their expected performance. The four new and two existing approaches are compared on several metrics of search space and planning overhead.
@inproceedings{ijcai1995p209,
title = {Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner},
author = {Srinivasan, Raghavan and Howe, Adele E.},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {1620--1625},
year = {1995},
note = {Planning},
url = {https://ijcai.org/proceedings/1995/209},
}
TY - CPAPER TI - Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner AU - Srinivasan, Raghavan AU - Howe, Adele E. T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 1620 EP - 1625 UR - https://ijcai.org/proceedings/1995/209 ER -Copied
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