Exact Algorithms and Lower Bounds for Forming Coalitions of Constrained Maximum Size

Abstract

Imagine we want to split a group of agents into teams in the most efficient way, considering that each agent has their own preferences about their teammates. This scenario is modeled by the extensively studied Coalition Formation problem. Here, we study a version of this problem where each team must additionally be of bounded size. We conduct a systematic algorithmic study, providing several intractability results as well as multiple exact algorithms that scale well as the input grows (FPT), which could prove useful in practice. Our main contribution is an algorithm that deals efficiently with tree-like structures (bounded treewidth) for ``small'' teams. We complement this result by proving that our algorithm is asymptotically optimal. Particularly, there can be no algorithm that vastly outperforms the one we present, under reasonable theoretical assumptions, even when considering star-like structures (bounded vertex cover number).

Cite

Text

Fioravantes et al. "Exact Algorithms and Lower Bounds for Forming Coalitions of Constrained Maximum Size." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I13.33514

Markdown

[Fioravantes et al. "Exact Algorithms and Lower Bounds for Forming Coalitions of Constrained Maximum Size." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/fioravantes2025aaai-exact/) doi:10.1609/AAAI.V39I13.33514

BibTeX

@inproceedings{fioravantes2025aaai-exact,
  title     = {{Exact Algorithms and Lower Bounds for Forming Coalitions of Constrained Maximum Size}},
  author    = {Fioravantes, Foivos and Gahlawat, Harmender and Melissinos, Nikolaos},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {13847-13855},
  doi       = {10.1609/AAAI.V39I13.33514},
  url       = {https://mlanthology.org/aaai/2025/fioravantes2025aaai-exact/}
}