Mechanisms That Play a Game, Not Toss a Coin
Abstract
Randomized mechanisms can have good normative properties compared to their deterministic counter-parts. However, randomized mechanisms are problematic in several ways such as in their verifiability. We propose here to de-randomize such mechanisms by having agents play a game instead of tossing a coin. The game is designed so agents play randomly, and this play injects “randomness” into the mechanism. Surprisingly this de-randomization retains many of the good normative properties of the original randomized mechanism but gives a mechanism that is deterministic and easy, for instance, to audit. We consider three general purpose methods to de-randomize mechanisms, and apply these to six different domains: voting, facility location, task allocation, school choice, peer selection, and resource allocation. We propose a number of novel de-randomized mechanisms for these six domains with good normative properties (such as equilibria in which agents sincerely report preferences over the original problem). In one domain, we additionally show that a new and desirable normative property emerges as a result of de-randomization.property emerges as a result of de-randomization.
BibTeX
@inproceedings{ijcai2024p333,
title = {Mechanisms That Play a Game, Not Toss a Coin},
author = {Walsh, Toby},
booktitle = {Proceedings of the Thirty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-24}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Kate Larson},
pages = {3005--3013},
year = {2024},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2024/333},
url = {https://doi.org/10.24963/ijcai.2024/333},
}