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Details for article 5 of 12 found articles
| Title: |
FLAP: Applying least-commitment in forward-chaining planning |
| Author: |
Sapena, Oscar Onaindia, Eva Torreño, Alejandro |
| Appeared in: |
AI communications |
| Paging: | Volume 28 (2014) nr. 1 pages 5-20 |
| Year: |
2014-09-10 |
| Contents: |
In this paper, we present FLAP, a partial-order planner that accurately applies the least-commitment principle that governs traditional partial-order planning. FLAP fully exploits the partial ordering among actions of a plan and hence it solves more problems than other similar approaches. The search engine of FLAP uses a combination of different state-based heuristics and applies a parallel search technique to diversify the search in different directions when a plateau is found. In the experimental evaluation, we compare FLAP with OPTIC, LPG-td and TFD, three state-of-the-art non-linear planners. The results show that FLAP outperforms these planners in terms of number of problems solved; in addition, the plans of FLAP represent a good trade-off between quality and computational time. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 5 of 12 found articles
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