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Type | Conference or Workshop Paper |
Scope | Discipline-based scholarship |
Published in Proceedings | Yes |
Title | Cuilt: a Scalable, Mix-and-Match Framework for Local Iterative Approximate Best-Response Algorithms |
Organization Unit |
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Authors |
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Editors |
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Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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ISBN | 978-1-61499-671-2 (print) | 978-1-61499-672-9 (online) |
ISSN | 0922-6389 |
Page Range | 1660 - 1661 |
Event Title | 22nd European Conference on Artificial Intelligence |
Event Type | conference |
Event Location | The Hague, The Netherlands |
Event Start Date | August 29 - 2016 |
Event End Date | September 2 - 2016 |
Series Name | Frontiers in Artificial Intelligence and Applications |
Number | 285 |
Publisher | I O S Press |
Abstract Text | Many real-world tasks can be modeled as constraint optimization problems. To ensure scalability and mapping to distributed scenarios, distributed constraint optimization problems (DCOPs) have been proposed, where each variable is locally controlled by its own agent. Most practical applications prefer approximate local iterative algorithms to reach a locally optimal and sufficiently good solution fast. Most implementations presented in the literature, however, only explored small-sized problems, typically up to 100 agents/variables. We implement CUILT, a scalable mix-and-match framework for Local Iterative Approximate Best-Response Algorithms for DCOPs, using the graph processing framework SIGNAL/COLLECT, where each agent is modeled as a vertex and communication pathways are represented as edges. Choosing this abstraction allows us to exploit the generic graph-oriented distribution/optimization heuristics and makes our proposed framework scalable, configurable, as well as extensible. We found that this approach allows us to scale to problems more than 3 orders of magnitude larger than results commonly published so far, to easily combine algorithms by mixing and matching, and to run the algorithms fast, in a parallel fashion. |
Free access at | DOI |
Official URL | http://ebooks.iospress.com/volumearticle/44969 |
Digital Object Identifier | 10.3233/978-1-61499-672-9-1660 |
PubMed ID | http://ebooks.iospress.com/volumearticle/44969 |
Other Identification Number | merlin-id:13478 |
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