Group Activity Selection on Social Networks

Abstract

We propose a new variant of the group activity selection problem (GASP), where the agents are placed on a social network and activities can only be assigned to connected subgroups. We show that if multiple groupscan simultaneously engage in the same activity, finding a stable outcome is easy as long as the networkis acyclic. In contrast, if each activity can be assigned to a single group only, finding stable outcomes becomes computationally intractable, even if the underlying network is very simple: the problem of determining whether a given instance of a GASP admits a Nash stable outcome turns out to be NP-hard when the social network is a path, a star, or if the size of each connected component is bounded by a constant.On the other hand, we obtain fixed-parameter tractability results for this problem with respectto the number of activities.

Cite

Text

Igarashi et al. "Group Activity Selection on Social Networks." AAAI Conference on Artificial Intelligence, 2017. doi:10.1609/AAAI.V31I1.10617

Markdown

[Igarashi et al. "Group Activity Selection on Social Networks." AAAI Conference on Artificial Intelligence, 2017.](https://mlanthology.org/aaai/2017/igarashi2017aaai-group/) doi:10.1609/AAAI.V31I1.10617

BibTeX

@inproceedings{igarashi2017aaai-group,
  title     = {{Group Activity Selection on Social Networks}},
  author    = {Igarashi, Ayumi and Peters, Dominik and Elkind, Edith},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {565-571},
  doi       = {10.1609/AAAI.V31I1.10617},
  url       = {https://mlanthology.org/aaai/2017/igarashi2017aaai-group/}
}