Stability and Efficiency in Hedonic Project Games
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 401-409.
https://doi.org/10.24963/ijcai.2026/46
Keywords
- Agent-based and Multi-agent Systems: Resource allocation
- Agent-based and Multi-agent Systems: Coordination and cooperation
- Agent-based and Multi-agent Systems: Agent theories and models
- Game Theory and Economic Paradigms: Cooperative games
- Game Theory and Economic Paradigms: Noncooperative games
Abstract
We introduce Hedonic Project Games, a model in which agents choose projects with divisible rewards while holding subjective preferences over coalition composition. This framework captures a fundamental trade-off absent from existing models: agents care simultaneously about who they collaborate with and what they work on. We study three stability notions: classical Nash Stability and two refinements, Joining Stability and Leaving Stability, which account for the welfare of both the deviating agent and the affected coalition members. We evaluate the efficiency of stable outcomes using the Price of Anarchy and Price of Stability, comparing the social welfare of stable outcomes to that of an optimal allocation. While stable outcomes may not exist in general, we identify broad and natural preference classes in which stability and efficiency improve significantly. In particular, under monotonic-decreasing preferences in coalition size, Nash and joining stability coincide and are guaranteed to exist, whereas leaving stability may fail. Under per-capita non-decreasing preferences, socially optimal outcomes are always Nash stable and coincide with leaving stability, although equilibrium inefficiency remains unbounded. Experiments on synthetic and real-world data support the theoretical efficiency results.
@inproceedings{ijcai2026p46,
title = {Stability and Efficiency in Hedonic Project Games},
author = {Valizadeh, Jaber and Zhang, Dongmo and Mubin, Omar},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {401--409},
year = {2026},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2026/46},
url = {https://doi.org/10.24963/ijcai.2026/46},
}
TY - CPAPER TI - Stability and Efficiency in Hedonic Project Games AU - Valizadeh, Jaber AU - Zhang, Dongmo AU - Mubin, Omar T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 401 EP - 409 DO - 10.24963/ijcai.2026/46 UR - https://doi.org/10.24963/ijcai.2026/46 ER -Copied
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