In this paper, an agent-based architecture devised
to perform experiments on hierarchical planning is described.
The planning activity results from the interaction of a
community of agents, some of them being explicitly devoted to
embed one or more existing planners. The proposed
architecture allows to exploit the characteristics of any external
planner, under the hypothesis that a suitable wrapper –in form
of planning agent– is provided. An implementation of the
architecture, able to embed one planner of the graphplan
family, has been used to directly assess whether or not
abstraction mechanisms can help to reduce the time complexity
of the search on specific domains. Some preliminary
experiments are reported, focusing on problems taken from the
AIPS 2002, 2000 and 1998 planning competitions. Comparative
results, obtained by assessing the performances of the selected
planner (used first in a stand-alone configuration and then
embedded into the proposed multi-agent architecture), put into
evidence that abstraction may significantly speed up the search
