Automatic generation of macro-operators from static domain analysis

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. 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. In particular, a preliminary release of a system devised to automatically generate abstraction hierachies has been implemented. The system is able to take into account also state invariants, to resolve ambiguities that may arise while performing abstraction. Experimental results highlight the ability of the system to identify suitable macro-operators, used as a starting point for populating the abstract level. Such macro-operators usually represent good alternatives to those extracted by a knowledge engineer after a thorough (and sometimes painful!) domain analysis.