FACS: Fast Code-Based Algorithm for Coalition Structure Generation (Student Abstract)

Redha Taguelmimt, Samir Aknine, Djamila Boukredera, Narayan Changder

AAAI 2021 pp. 15907-15908

doi:10.1609/AAAI.V35I18.17950 /aaai/2021/taguelmimt2021aaai-facs/

Abstract

In this paper, we propose a new algorithm for the Coalition Structure Generation (CSG) problem that can be run with more than 28 agents while using a complete set of coalitions as input. The current state-of-the-art limit for exact algorithms to solve the CSG problem within a reasonable time is 27 agents. Our algorithm uses a novel representation of the search space and a new code-based search technique. We propose an effective heuristic search method to efficiently explore the space of coalition structures using our code based technique and show that our method outperforms existing state-of-the-art algorithms by multiple orders of magnitude.

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Cite

Text

Taguelmimt et al. "FACS: Fast Code-Based Algorithm for Coalition Structure Generation (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I18.17950

Markdown

[Taguelmimt et al. "FACS: Fast Code-Based Algorithm for Coalition Structure Generation (Student Abstract)." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/taguelmimt2021aaai-facs/) doi:10.1609/AAAI.V35I18.17950

BibTeX

@inproceedings{taguelmimt2021aaai-facs,
  title     = {{FACS: Fast Code-Based Algorithm for Coalition Structure Generation (Student Abstract)}},
  author    = {Taguelmimt, Redha and Aknine, Samir and Boukredera, Djamila and Changder, Narayan},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {15907-15908},
  doi       = {10.1609/AAAI.V35I18.17950},
  url       = {https://mlanthology.org/aaai/2021/taguelmimt2021aaai-facs/}
}