Total Order Planning Is More Efficient than We Thought
Abstract
In this paper, we present VVPLAN, a planner based on a classical state space search algorithm. The language used for domain and problem representation is ADL (Pednault 1989). We have compared VVPLAN to UCPOP (Penberthy and Weld 1992)(Weld 1994), a planner that admits the same representation language. Our experiments prove that such an algorithm is often more efficient than a planner based on a search in the space of partial plans. This result is achieved as soon as we introduce in VVPLAN’s algorithm a loop test relating to previously visited states. In particular domains, VVPLAN can also outperform IPP (Koehler et al. 1997), which makes a planning graph analysis as GRAPHPLAN. We present here the details of our comparison with UCPOP, the results we obtain and our conclusions.
Cite
Text
Vidal and Régnier. "Total Order Planning Is More Efficient than We Thought." AAAI Conference on Artificial Intelligence, 1999.Markdown
[Vidal and Régnier. "Total Order Planning Is More Efficient than We Thought." AAAI Conference on Artificial Intelligence, 1999.](https://mlanthology.org/aaai/1999/vidal1999aaai-total/)BibTeX
@inproceedings{vidal1999aaai-total,
title = {{Total Order Planning Is More Efficient than We Thought}},
author = {Vidal, Vincent and Régnier, Pierre},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1999},
pages = {591-596},
url = {https://mlanthology.org/aaai/1999/vidal1999aaai-total/}
}