Towards a Formal Framework for Hybrid Planning in Self-Adaptation
Ashutosh Pandey,
Ivan Ruchkin,
Bradley Schmerl and
Javier Cámara.
In Proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017), Buenos Aires, Argentina, 22-23 May 2017.
Online links:
Abstract
Approaches to self-adaptation face a fundamental
trade-off between quality and timeliness in decision-making. Due
to this trade-off, designers of self-adaptive systems often have
to find a fixed and suboptimal compromise between these two
requirements. Recent work has proposed the hybrid planning approach
that can resolve this trade-off dynamically and potentially
in an optimal way. The promise of hybrid planning is to combine
multiple planners at run time to produce adaptation plans of
the highest quality within given time constraints. However, since
decision-making approaches are complex and diverse, the problem
of combining them is even more difficult, and no frameworks for
hybrid planning. This paper makes an important step in simplifying
the problem of hybrid planning by formalizing it and decomposing
it into four simpler subproblems. These formalizations
will serve as a foundation for creating and evaluating engineering
solutions to the hybrid planning problem. |
Keywords: Planning, Self-adaptation.
@InProceedings{2017:Pandey:HybridPlanningFormalization,
AUTHOR = {Pandey, Ashutosh and Ruchkin, Ivan and Schmerl, Bradley and C\'{a}mara, Javier},
TITLE = {Towards a Formal Framework for Hybrid Planning in Self-Adaptation},
YEAR = {2017},
MONTH = {22-23 May},
BOOKTITLE = {Proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2017)},
ADDRESS = {Buenos Aires, Argentina},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/hybrid-planning-seams2017.pdf},
ABSTRACT = {Approaches to self-adaptation face a fundamental
trade-off between quality and timeliness in decision-making. Due
to this trade-off, designers of self-adaptive systems often have
to find a fixed and suboptimal compromise between these two
requirements. Recent work has proposed the hybrid planning approach
that can resolve this trade-off dynamically and potentially
in an optimal way. The promise of hybrid planning is to combine
multiple planners at run time to produce adaptation plans of
the highest quality within given time constraints. However, since
decision-making approaches are complex and diverse, the problem
of combining them is even more difficult, and no frameworks for
hybrid planning. This paper makes an important step in simplifying
the problem of hybrid planning by formalizing it and decomposing
it into four simpler subproblems. These formalizations
will serve as a foundation for creating and evaluating engineering
solutions to the hybrid planning problem.},
KEYWORDS = {Planning, Self-adaptation} }
|