From Monopoly to Competition: Optimal Contests Prevail
Authors: Xiaotie Deng, Yotam Gafni, Ron Lavi, Tao Lin, Hongyi Ling
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study competition among contests in a general model that allows for an arbitrary and heterogeneous space of contest design and symmetric contestants. The goal of the contest designers is to maximize the contestants sum of efforts. Our main result shows that optimal contests in the monopolistic setting (i.e., those that maximize the sum of efforts in a model with a single contest) form an equilibrium in the model with competition among contests. Under a very natural assumption these contests are in fact dominant, and the equilibria that they form are unique. Moreover, equilibria with the optimal contests are Pareto-optimal even in cases where other equilibria emerge. In many natural cases, they also maximize the social welfare. (Abstract) |
| Researcher Affiliation | Academia | Xiaotie Deng1, Yotam Gafni2, Ron Lavi3, Tao Lin4, Hongyi Ling 5 1Center on Frontiers of Computing Studies, Department of Computer Science, Peking University, 2Technion Israel Institute of Technology, 3University of Bath, UK, 4School of Engineering and Applied Sciences, Harvard University, 5ETH Zurich |
| Pseudocode | No | The paper is theoretical and does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not use or mention any datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation with dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware specifications used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training settings. |