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Article #9059

Planner Implementation

#9059
From: Steve Woods
Date: Fri, 06 Sep 1991 01:27
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I have recently completed a masters thesis entitled "An Implementation
and Evaluation of a Hierarchical Nonlinear Planner".  The abstract
follows.  If anyone is interested, the thesis, implementation in
Common Lisp w/ users-manual, and a paper dealing with the results in
about 14 pages is available via anonymous ftp from:

csis.dit.csiro.au

the directory you want is  pub/steve   and a README file there will
summarize the directory contents.  Please Email me if you FTP a copy
of the planner.

Note that this work builds upon TWEAK as described by David Chapman,
and embodies the ABTWEAK planner first described by Qiang Yang and
Josh Tenenberg.

Steve Woods

THESIS ABSTRACT

Planning is the process of generating sequences of actions in order to provide
a method for agents to modify the state of the world in which they
exist. It is well known that the application of abstraction can
greatly reduce the search involved in creating plans. In this talk, an
empirical evaluation of several different approaches to reducing
search in \abtweak, an abstract nonlinear planning system, are presented. 

To solve a complex problem using abstraction, one would like to
protect parts of the abstract solution that have already been completed 
during the abstract plan refinement.  However, it has not been well understood 
how this protection can be done profitably; some subgoal protection may indeed
result in a decrease in efficiency.  The Monotonic Property has been proposed
as a form of goal protection in  abstract planning.  Different versions of this
property are investigated with respect to their effect on planning performance
in  several domains.  Furthermore, a series of empirical tests of the
utility of the properties are presented, along with an evaluation of
different search strategies for abstract planning.  

In addition, we present a novel abstract planning control strategy known as
\leftwedge. This strategy adds a depth-first flavor to a complete search
strategy by taking advantage of the fact that less abstract
solutions are generally closer to a concrete level solution than more abstract
ones. The relative benefit of this approach under various criticality
assignments is demonstrated through comparisons with breadth-first strategy.
Furthermore, two subgoal selection strategies are presented and compared
empirically. 



--
Steven.Woods@csis.dit.csiro.au                  Phone +61-6-2750927     Fax +61-6-2571052
CSIRO Division of Information Technology        ANU, Acton Canberra ACT AUSTRALIA.
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From: sgwoods@vela.csis.dit.csiro.au (Steve Woods)
Newsgroups: comp.ai,aus.ai
Subject: Planner Implementation
Message-ID: <1991Sep6.012716.29253@csis.dit.csiro.au>
Date: 6 Sep 91 01:27:16 GMT
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