Solving DisCSPs with Penalty Driven Search

Abstract

We introduce the Distributed, Penalty-driven Local search algorithm
\n(DisPeL) for solving Distributed Constraint Satisfaction
\nProblems. DisPeL is a novel distributed iterative improvement
\nalgorithm which escapes local optima by the use
\nof both temporary and incremental penalties and a tabu-like
\nno-good store. We justify the use of these features and provide
\nempirical results which demonstrate the competitiveness
\nof the algorithm.

Cite

Text

Basharu et al. "Solving DisCSPs with Penalty Driven Search." AAAI Conference on Artificial Intelligence, 2005.

Markdown

[Basharu et al. "Solving DisCSPs with Penalty Driven Search." AAAI Conference on Artificial Intelligence, 2005.](https://mlanthology.org/aaai/2005/basharu2005aaai-solving/)

BibTeX

@inproceedings{basharu2005aaai-solving,
  title     = {{Solving DisCSPs with Penalty Driven Search}},
  author    = {Basharu, Muhammed and Arana, Inés and Ahriz, Hatem},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2005},
  pages     = {47-52},
  url       = {https://mlanthology.org/aaai/2005/basharu2005aaai-solving/}
}