Skip to Main content Skip to Navigation
Conference papers

Filtering, Decomposition and Search Space Reduction for Optimal Sequential Planning

Abstract : We present in this paper a hybrid planning system which combines constraint satisfaction techniques and planning heuris-tics to produce optimal sequential plans. It integrates its own consistency rules and filtering and decomposition mechanisms suitable for planning. Given a fixed bound on the plan length, our planner works directly on a structure related to Graphplan's planning graph. This structure is incrementally built: Each time it is extended, a sequential plan is searched. Different search strategies may be employed. Currently, it is a forward chaining search based on problem decomposition with action sets partitioning. Various techniques are used to reduce the search space, such as memorizing nogood states or estimating goals reachability. In addition, the planner implements two different techniques to avoid enumerating some equivalent action sequences. Empirical evaluation shows that our system is very competitive on many problems, especially compared to other optimal sequential planners.
Document type :
Conference papers
Complete list of metadatas

Cited literature [13 references]  Display  Hide  Download

https://hal-amu.archives-ouvertes.fr/hal-02471078
Contributor : Stéphane Grandcolas <>
Submitted on : Friday, February 7, 2020 - 5:16:37 PM
Last modification on : Monday, March 30, 2020 - 8:41:29 AM
Long-term archiving on: : Friday, May 8, 2020 - 5:47:11 PM

File

article-aaai.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02471078, version 1

Citation

Stéphane Grandcolas, Cyril Pain-Barre. Filtering, Decomposition and Search Space Reduction for Optimal Sequential Planning. AAAI, Jul 2007, Vancouver, Canada. ⟨hal-02471078⟩

Share

Metrics

Record views

12

Files downloads

8