Infinite-horizon proactive dynamic DCOPs

Khoi D. Hoang, Ping Hou, Ferdinando Fioretto, William Yeoh, Roie Zivan, Makoto Yokoo

Research output: Chapter in Book/Entry/PoemConference contribution

19 Scopus citations


The Distributed Constraint Optimization Problem (DCOP) formulation is a powerful tool for modeling multi-Agent coordination problems. Researchers have recently extended this model to Proactive Dynamic DCOPs (PD-DCOPs) to capture the inherent dynamism present in many coordination problems. The PD-DCOP formulation is a finite-horizon model that assumes a finite horizon is known a priori. It ignores changes to the problem after the horizon and is thus not guaranteed to find optimal solutions for infinite-horizon problems, which often occur in the real world. Therefore, we (i) propose the Infinite-Horizon PD-DCOP (IPD- DCOP) model, which extends PD-DCOPs to handle infinite horizons', (ii) exploit the convergence properties of Markov chains to determine the optimal solution to the problem after it has converged; (Hi) propose three distributed greedy algorithms to solve IPD-DCOPs; (iv) provide theoretical quality guarantees on the new model; and (v) empirically evaluate both proactive and reactive algorithms to determine the tradeoffs between the two classes. The final contribution is important as, thus far. researchers have exclusively evaluated the two classes of algorithms in isolation. As a result, it is difficult to identify the characteristics of problems that they excel in. Our results arc the first in this important direction.

Original languageEnglish (US)
Title of host publication16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
EditorsEdmund Durfee, Sanmay Das, Kate Larson, Michael Winikoff
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Number of pages9
ISBN (Electronic)9781510855076
StatePublished - 2017
Externally publishedYes
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: May 8 2017May 12 2017

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914


Conference16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
CitySao Paulo


  • Distributed constraint optimization
  • Dynamic dcops
  • Stochastic dcops

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering


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