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Author, Editor

Author(s):

Hoffmann, Jörg
Sabharwal, Ashish
Domshlak, Carmel

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Not MPG Author(s):

Sabharwal, Ashish
Domshlak, Carmel

Editor(s):

Long, Derek
Smith, Stephen F.
Borrajo, Daniel
McCluskey, Lee

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dblp
dblp
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Not MPII Editor(s):

Long, Derek
Smith, Stephen F.
Borrajo, Daniel
McCluskey, Lee

BibTeX cite key*:

HoffmannEtAl2006b

Title, Booktitle

Title*:

Friends or Foes? An AI Planning Perspective on Abstraction and Search

Booktitle*:

Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006)

Event, URLs

URL of the conference:

http://icaps06.icaps-conference.org/

URL for downloading the paper:


Event Address*:

The English Lake District

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

6 June 2006

Event End Date:

10 June 2006

Publisher

Name*:

AAAI

URL:

http://www.aaai.org/

Address*:

Menlo Park, USA

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:


Pages:

294-303

Year*:

2006

VG Wort Pages:


ISBN/ISSN:

978-1-57735-270-9

Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

There is increasing awareness that planning and model checking are closely related fields. Abstraction means to perform search in an over-approximation of the original problem instance, with a potentially much smaller state space. This is the most essential method in model checking. One would expect that it can also be made successful in planning. We show, however, that this is likely to not be the case. The main reason is that, while in model checking one traditionally uses blind search to exhaust the state space and prove the absence of solutions, in planning informed search is used to find solutions. We give an exhaustive theoretical and practical account of the use of abstraction in planning. For all abstraction (over-approximation) methods known in planning, we prove that they cannot improve the best-case behavior of informed search. While this is easy to see for heuristic search, we were quite surprised to find that it also holds, in most cases, for the resolution-style proofs of unsolvability underlying SAT-based optimal planners. This result is potentially relevant also for model checking, where SAT-based techniques have recently been combined with abstraction. Exploring the issue in planning practice, we find that even hand-made abstractions do not tend to improve the performance of planners, unless the attacked task contains huge amounts of irrelevance. We relate these findings to the kinds of application domains that are typically addressed in model checking.

URL for the Abstract:

http://www.aaai.org/Library/ICAPS/2006/icaps06-030.php



Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Programming Logics Group

Audience:

Expert

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, CCL bibliography, VG Wort



BibTeX Entry:

@INPROCEEDINGS{HoffmannEtAl2006b,
AUTHOR = {Hoffmann, J{\"o}rg and Sabharwal, Ashish and Domshlak, Carmel},
EDITOR = {Long, Derek and Smith, Stephen F. and Borrajo, Daniel and McCluskey, Lee},
TITLE = {Friends or Foes? An {AI} Planning Perspective on Abstraction and Search},
BOOKTITLE = {Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006)},
PUBLISHER = {AAAI},
YEAR = {2006},
PAGES = {294--303},
ADDRESS = {The English Lake District},
ISBN = {978-1-57735-270-9},
}


Entry last modified by Uwe Brahm, 01/28/2008
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Editor(s)
Jörg Hoffmann
Created
02/13/2006 11:39:23 AM
Revisions
3.
2.
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0.
Editor(s)
Uwe Brahm
Uwe Brahm
Uwe Brahm
Jörg Hoffmann
Edit Dates
2007-04-24 18:10:37
2007-04-24 18:03:14
2007-04-24 17:56:39
02/13/2006 11:39:23 AM
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