The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Distributed constraint programming with agents

På svenska

Author

  • Carl Christian Rolf
  • Krzysztof Kuchcinski

Editor

  • Abbas Manthiri. M

Summary, in English

Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes.



By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP). By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce communication between agents.



Our experiments show that both global constraints and advanced search schemes are necessary to optimize job shop schedules using DisCSP.

Publishing year

2011

Language

English

Pages

320-331

Publication/Series

Lecture notes in computer science

Volume

6943

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Science

Conference name

International Conference on Adaptive and Intelligent Systems (ICAIS 2011)

Conference date

2011-09-06 - 2011-09-08

Conference place

Klagenfurt, Austria

Status

Published

Research group

  • ESDLAB

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISBN: 978-3-642-23857-4
  • ISBN: 978-3-642-23857-4