Newsgroups: comp.ai.jair.announce
Path: cantaloupe.srv.cs.cmu.edu!bb3.andrew.cmu.edu!nntp.sei.cmu.edu!cis.ohio-state.edu!math.ohio-state.edu!howland.reston.ans.net!swrinde!elroy.jpl.nasa.gov!ames!eos!kronos.arc.nasa.gov!jair-ed
From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, Building and Refining Abstract ...
Message-ID: <1995Jul31.204639.4352@ptolemy-ethernet.arc.nasa.gov>
Originator: jair-ed@polya.arc.nasa.gov
Lines: 40
Sender: usenet@ptolemy-ethernet.arc.nasa.gov (usenet@ptolemy.arc.nasa.gov)
Nntp-Posting-Host: polya.arc.nasa.gov
Organization: NASA/ARC Computational Sciences Division
Date: Mon, 31 Jul 1995 20:46:39 GMT
Approved: jair-ed@ptolemy.arc.nasa.gov

JAIR is pleased to announce the publication of the following article:

Bergmann, R. and Wilke, W. (1995)
  "Building and Refining Abstract Planning Cases by Change of 
   Representation Language", Volume 3, pages 53-118.
   PostScript: volume3/bergmann95a.ps (850K)
	       compressed, volume3/bergmann95a.ps.Z (302K)
   Online Appendix: volume3/bergmann95a-appendix (11K) data file


   Abstract: Abstraction is one of the most promising approaches to improve the
   performance of problem solvers. In several domains abstraction by
   dropping sentences of a domain description -- as used in most
   hierarchical planners -- has proven useful. In this paper we present
   examples which illustrate significant drawbacks of abstraction by
   dropping sentences. To overcome these drawbacks, we propose a more
   general view of abstraction involving the change of representation
   language. We have developed a new abstraction methodology and a
   related sound and complete learning algorithm that allows the complete
   change of representation language of planning cases from concrete to
   abstract.  However, to achieve a powerful change of the representation
   language, the abstract language itself as well as rules which describe
   admissible ways of abstracting states must be provided in the domain
   model. This new abstraction approach is the core of Paris (Plan
   Abstraction and Refinement in an Integrated System), a system in which
   abstract planning cases are automatically learned from given concrete
   cases. An empirical study in the domain of process planning in
   mechanical engineering shows significant advantages of the proposed
   reasoning from abstract cases over classical hierarchical planning.
   
The PostScript file is available via:
   
 -- comp.ai.jair.papers

 -- World Wide Web: The URL for our World Wide Web server is
       http://www.cs.washington.edu/research/jair/home.html

 -- Anonymous FTP from either of the two sites below:
      CMU:   p.gp.cs.cmu.edu        directory: /usr/jair/pub/volume3
      Genoa: ftp.mrg.dist.unige.it  directory:  pub/jair/pub/volume3

 -- automated email. Send mail to jair@cs.cmu.edu or jair@ftp.mrg.dist.unige.it
    with the subject AUTORESPOND, and the body GET VOLUME3/FILE-NM
    (e.g., GET VOLUME3/MOONEY95A.PS)
    Note: Your mailer might find our files too large to handle. Also, note  
    that compressed files cannot be emailed, since they are binary files.

 -- JAIR Gopher server: At p.gp.cs.cmu.edu, port 70. 

For more information about JAIR, check out our WWW or FTP sites, or
send electronic mail to jair@cs.cmu.edu with the subject AUTORESPOND
and the message body HELP, or contact jair-ed@ptolemy.arc.nasa.gov.



