@article{keyhere,
title = {In defense of PDDL axioms},
author = {Sylvie Thiebaux and Jorg Hoffmann and Bernhard Nebel},
journal = {Artificial Intelligence},
month = {#oct#},
number = {1-2},
pages = {38--69},
url = {http://www.sciencedirect.com/science/article/B6TYF-4GP1VMJ-1/2/4be3aaa78a5e4407ace7425993abafdc},
volume = {168},
year = {2005},
description = {ScienceDirect - Artificial Intelligence : In defense of PDDL axioms},
abstract = {There is controversy as to whether explicit support for pddl-like axioms and derived predicates is needed for planners to handle real-world domains effectively. Many researchers have deplored the lack of precise semantics for such axioms, while others have argued that it might be best to compile them away. We propose an adequate semantics for pddl axioms and show that they are an essential feature by proving that it is impossible to compile them away if we restrict the growth of plans and domain descriptions to be polynomial. These results suggest that adding a reasonable implementation to handle axioms inside the planner is beneficial for the performance. Our experiments confirm this suggestion.},
keywords = {Classical Expressive PDDL planning power }
}
::