Approximation algorithms for scheduling unrelated parallel machines
Mathematical Programming: Series A and B
Pareto optimality in coalition formation
SAGT'11 Proceedings of the 4th international conference on Algorithmic game theory
Computational Aspects of Cooperative Game Theory (Synthesis Lectures on Artificial Inetlligence and Machine Learning)
Matching models for preference-sensitive group purchasing
Proceedings of the 13th ACM Conference on Electronic Commerce
Fully proportional representation as resource allocation: approximability results
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We consider a setting where one has to organize one or several group activities for a set of agents. Each agent will participate in at most one activity, and her preferences over activities depend on the number of participants in the activity. The goal is to assign agents to activities based on their preferences. We put forward a general model for this setting, which is a natural generalization of anonymous hedonic games. We then focus on a special case of our model, where agents' preferences are binary, i.e., each agent classifies all pairs of the form "(activity, group size)" into ones that are acceptable and ones that are not. We formulate several solution concepts for this scenario, and study them from the computational point of view, providing hardness results for the general case as well as efficient algorithms for settings where agents' preferences satisfy certain natural constraints.