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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Exploring Hybrid Iterative Approximate Best-Response Algorithms for Solving DCOPs
Organization Unit
  • Coralia-Mihaela Verman
  • Philip Stutz
  • Robin Hafen
  • Abraham Bernstein
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Event Title International Workshop on Optimisation in Multi-agent Systems
Event Type workshop
Event Location Singapore
Event Start Date May 10 - 2016
Event End Date May 10 - 2016
Publisher s.n.
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. The Iterative Approximate Best-Response Algorithms can be decomposed in three types of components and mixing different components allows to create hybrid algorithms. We implement a mix-and-match framework for these algorithms, 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 configurable as well as extensible. It allows us to easily recombine the components, create and exhaustively evaluate possible hybrid algorithms.
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Other Identification Number merlin-id:13269
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