Managing Uncertainty in Self-Adaptive Systems with Plan Reuse and Stochastic Search
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Kinneer:2018:SEAMS,
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author = "Cody Kinneer and Zack Coker and Jiacheng Wang and
David Garlan and Claire {Le Goues}",
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title = "Managing Uncertainty in Self-Adaptive Systems with
Plan Reuse and Stochastic Search",
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booktitle = "13th International Symposium on Software Engineering
for Adaptive and Self-Managing Systems, SEAMS 2018",
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year = "2018",
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editor = "Danny Weyns",
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pages = "40--50",
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address = "Gothenburg, Sweden",
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month = may # " 28-29",
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publisher = "ACM",
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keywords = "genetic algorithms, genetic programming, SBSE, plan
reuse, self-* systems, planning, uncertainty, cloud
services",
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ISSN = "2157-2305",
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URL = "http://acme.able.cs.cmu.edu/pubs/uploads/pdf/seams-uncertainty-kinneerpdf.pdf",
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URL = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=8595379",
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DOI = "doi:10.1145/3194133.3194145",
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size = "11 pages",
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abstract = "Many software systems operate in environments where
change and uncertainty are the rule, rather than
exceptions. Techniques for self-adaptation allow these
systems to automatically respond to environmental
changes, yet they do not handle changes to the adaptive
system itself, such as the addition or removal of
adaptation tactics. Instead, changes in a self-adaptive
system often require a human planner to redo an
expensive planning process to allow the system to
continue satisfying its quality requirements under
different conditions; automated techniques typically
must replan from scratch. We propose to address this
problem by reusing prior planning knowledge to adapt in
the face of unexpected situations. We present a planner
based on genetic programming that reuses existing
plans. While reuse of material in genetic algorithms
has recently applied successfully in the area of
automated program repair, we find that naively reusing
existing plans for self-star planning actually results
in a loss of utility. Furthermore, we propose a series
of techniques to lower the costs of reuse, allowing
genetic techniques to leverage existing information to
improve planning utility when replanning for unexpected
changes.",
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notes = "https://conf.researchr.org/home/seams-2018 Co-located
with ICSE 2018
The SEAMS 2018 proceedings are available as part of the
ICSE 2018 proceedings on the official ICSE 2018
webpage.
Also known as \cite{8595379}",
- }
Genetic Programming entries for
Cody Kinneer
Zack Coker
Jiacheng Wang
David Garlan
Claire Le Goues
Citations