Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner

Abstract

The search space in partial-order planning grows quickly with the number of subgoals and initial conditions, as well as less countable 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 commonalities 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. 1 Improving Search Efficiency in Planners Partial order planning is becoming a common method of planning. Unfortunately, but hardly unexpectedly, the search space in partial order planning expands quickly as the problem size increases. Unfortunately, but less expectedly, se...

Cite

Text

Srinivasan and Howe. "Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner." International Joint Conference on Artificial Intelligence, 1995.

Markdown

[Srinivasan and Howe. "Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/srinivasan1995ijcai-comparison/)

BibTeX

@inproceedings{srinivasan1995ijcai-comparison,
  title     = {{Comparison of Methods for Improving Search Efficiency in a Partial-Order Planner}},
  author    = {Srinivasan, Raghavan and Howe, Adele E.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1995},
  pages     = {1620-1626},
  url       = {https://mlanthology.org/ijcai/1995/srinivasan1995ijcai-comparison/}
}