Mechanisms That Play a Game, Not Toss a Coin

Authors: Toby Walsh

IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical 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. (From Abstract). Also, the paper presents multiple theorems and proofs (e.g., Theorem 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11), which are characteristics of theoretical research.
Researcher Affiliation Academia Toby Walsh AI Institute, UNSW Sydney tw@cse.unsw.edu.au
Pseudocode Yes Algorithm 1 Biased Min Work(m, ti j, bj)
Open Source Code No The paper does not mention the availability of source code or provide any links to code repositories.
Open Datasets No The paper is theoretical and does not involve empirical studies with datasets for training, validation, or testing.
Dataset Splits No The paper is theoretical and does not involve empirical studies with datasets for training, validation, or testing.
Hardware Specification No The paper is theoretical and does not mention any hardware specifications used for running experiments or simulations.
Software Dependencies No The paper is theoretical and does not list any specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and focuses on proposing and analyzing mechanisms, rather than detailing a specific experimental setup with hyperparameters or training configurations.