DJAO: A Communication-Constrained DCOP Algorithm That Combines Features of ADOPT and Action-GDL

Abstract

In this paper we propose a novel DCOP algorithm, called DJAO, that is able toefficiently find a solution with low communication overhead; this algorithm can be used for optimal and bounded approximate solutions by appropriately setting the error bounds. Our approach builds on distributed junction trees used in Action-GDL to represent independence relationsamong variables. We construct an AND/OR search space based on these junction trees.This new type of search space results in higher degrees for each OR node, consequently yielding a more efficient search graph in the distributed settings. DJAO uses a branch-and-bound search algorithm to distributedly find solutions within this search graph. We introduce heuristics to compute the upper and lower boundestimates that the search starts with, which is integral to our approach for reducing communication overhead. We empirically evaluate our approach in various settings.

Cite

Text

Kim and Lesser. "DJAO: A Communication-Constrained DCOP Algorithm That Combines Features of ADOPT and Action-GDL." AAAI Conference on Artificial Intelligence, 2014. doi:10.1609/AAAI.V28I1.9129

Markdown

[Kim and Lesser. "DJAO: A Communication-Constrained DCOP Algorithm That Combines Features of ADOPT and Action-GDL." AAAI Conference on Artificial Intelligence, 2014.](https://mlanthology.org/aaai/2014/kim2014aaai-djao/) doi:10.1609/AAAI.V28I1.9129

BibTeX

@inproceedings{kim2014aaai-djao,
  title     = {{DJAO: A Communication-Constrained DCOP Algorithm That Combines Features of ADOPT and Action-GDL}},
  author    = {Kim, Yoonheui and Lesser, Victor R.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2014},
  pages     = {2680-2687},
  doi       = {10.1609/AAAI.V28I1.9129},
  url       = {https://mlanthology.org/aaai/2014/kim2014aaai-djao/}
}