ML Anthology

Learning Hedonic Games

Jakub Sliwinski, Yair Zick
IJCAI 2017 pp. 2730-2736
doi:10.24963/IJCAI.2017/380 /ijcai/2017/sliwinski2017ijcai-learning/

Abstract

Coalitional stability in hedonic games has usually been considered in the setting where agent preferences are fully known. We consider the setting where agent preferences are unknown; we lay the theoretical foundations for studying the interplay between coalitional stability and (PAC) learning in hedonic games. We introduce the notion of PAC stability - the equivalent of core stability under uncertainty - and examine the PAC stabilizability and learnability of several popular classes of hedonic games.

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Text

Sliwinski and Zick. "Learning Hedonic Games." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/380

Markdown

[Sliwinski and Zick. "Learning Hedonic Games." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/sliwinski2017ijcai-learning/) doi:10.24963/IJCAI.2017/380

BibTeX

@inproceedings{sliwinski2017ijcai-learning,
  title     = {{Learning Hedonic Games}},
  author    = {Sliwinski, Jakub and Zick, Yair},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {2730-2736},
  doi       = {10.24963/IJCAI.2017/380},
  url       = {https://mlanthology.org/ijcai/2017/sliwinski2017ijcai-learning/}
}