A Generalization of Probabilistic Serial to Randomized Social Choice
Authors: Haris Aziz, Paul Stursberg
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present the egalitarian simultaneous reservation social decision scheme an extension of probabilistic serial to the more general setting of randomized social choice. We consider various desirable fairness, efficiency, and strategic properties of social decision schemes and show that egalitarian simultaneous reservation compares favorably against existing rules. Finally, we define a more general class of social decision schemes called simultaneous reservation, that contains egalitarian simultaneous reservation as well as the serial dictatorship rules. We show that outcomes of simultaneous reservation characterize efficiency with respect to a natural refinement of stochastic dominance. |
| Researcher Affiliation | Collaboration | Haris Aziz NICTA and UNSW, Sydney 2033, Australia haris.aziz@nicta.com.au Paul Stursberg Technische Universit at M unchen, 85748 Garching bei M unchen, Germany paul.stursberg@ma.tum.de |
| Pseudocode | Yes | Algorithm 1: The ESR algorithm. Algorithm 2: The function compute Lambda. |
| Open Source Code | No | The paper does not contain any statement about making its source code available or provide any links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not use or reference any datasets for empirical evaluation, so no information about publicly available training datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any computational experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper does not mention any specific software dependencies or version numbers. |
| Experiment Setup | No | The paper is theoretical and does not include details on experimental setup, hyperparameters, or training configurations. |