Paper Info
Title
A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software
Abstract
Self-adaptive software is a closed-loop system which aims at adjusting itself in response to changes at runtime. Such a system is required to monitor domain events, detect significant changes, decide how to react, and act in order to execute the decisions. This paper focuses on the deciding process particularly for application-level adaptation actions. For this purpose, a weighted voting mechanism has been proposed which makes decisions based on a Goal-Action- Attribute Model (GAAM). The decision-making algorithm traverses GAAM, determines activated goals and feasible actions for voting, and ultimately selects an action as the social choice. The proposed mechanism and GAAM are evaluated within a simulated model of a news web site.
Year
DOI
Venue
2007
10.1109/SASO.2007.4
SASO
Keywords
Field
DocType
self-adaptive software,activated goal,weighted voting mechanism,domain event,application-level adaptation action,deciding process,decision-making algorithm,proposed mechanism,action selection,closed-loop system,attribute model,adaptive systems,navigation,engines,knowledge representation,social choice,software engineering,voting,autonomous agents,simulation model
Social choice theory,Knowledge representation and reasoning,Voting,Self adaptive software,Computer science,Adaptive system,Weighted voting,Software,Artificial intelligence,Action selection,Machine learning
Conference
ISBN
Citations 
PageRank 
0-7695-2906-2
5
0.66
References 
Authors
4
2
Name
Order
Citations
PageRank
Mazeiar Salehie183134.30
Ladan Tahvildari2140868.51