Distance Preservation Games
Distance Preservation Games
Haris Aziz, Hau Chan, Patrick Lederer, Shivika Narang, Toby Walsh
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Main Track. Pages 3735-3743.
https://doi.org/10.24963/ijcai.2025/415
We introduce and analyze distance preservation games (DPGs). In DPGs, agents express ideal distances to other agents and need to choose locations in the unit interval while preserving their ideal distances as closely as possible. We analyze the existence and computation of location profiles that are jump stable (i.e., no agent can benefit by moving to another location) or welfare optimal for DPGs, respectively. Specifically, we prove that there are DPGs without jump stable location profiles and identify important cases where such outcomes always exist and can be computed efficiently. Similarly, we show that finding welfare optimal location profiles is NP-complete and present approximation algorithms for finding solutions with social welfare close to optimal. Finally, we prove that DPGs have a price of anarchy of at most 2.
Keywords:
Game Theory and Economic Paradigms: GTEP: Computational social choice
Game Theory and Economic Paradigms: GTEP: Cooperative games
Game Theory and Economic Paradigms: GTEP: Noncooperative games
