ECAI 2004 Conference Paper

[full paper]

Automatic Generation of Macro-Operators from Static Domain Analysis

Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu

The attempt of dealing with the complexity of planning tasks by resorting to abstraction techniques is a central issue in the field of automated planning. Although the generality of the approach has not been proved always useful on domains selected for benchmarking purposes, in our opinion it will play a central role as soon as the focus will move from artificial to real problems. In this case, it will be crucial to have a tool for automatically generating abstraction hierarchies from a domain description. This paper addresses the problem of how to identify macro operators starting from a ground-level description of a domain, to be used for generating useful abstract-level descriptions. Compared to our previous work, this paper reports a step further, in the direction of fully automatizing the process, from both a conceptual and pragmatic perspective. Conceptually, we refined the process of macro-operators extraction by dealing with the problem of parameters' unification through the exploitation of domain invariants. Pragmatically, we implemented a system that –given a description of the domain specified in PDDL 1.X– outputs a set of macro-operators to be used as a starting point for defining abstract operators. Experimental results highlight the ability of the system to identify suitable macro-operators that are usually good alternatives to those extracted by a knowledge engineer after a thorough (and sometimes painful!) domain analysis.

Keywords: Macro-operators, Automatic Domain Analysis, Planning by Abstraction

Citation: Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu: Automatic Generation of Macro-Operators from Static Domain Analysis. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.955-956.