Walrasian Dynamics in Multi-Unit Markets
Authors: Simina Brânzei, Aris Filos-Ratsikas1812-1819
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We prove that the mechanism converges from any starting profile when we have two buyers. Theorem 8 For n = 2 buyers, the best response dynamic of the ALL-OR-NOTHING mechanism converges to a Nash equilibrium from any initial strategy profile. We present the convergence results for values n = 25 and m = 20 and for two different choices of budgets, either drawn from [1, 50] or from [1, 120], but the mechanism actually always converges to a pure Nash equilibrium from any initial profile, for any choice of n and m that we have considered. We conclude with the following conjecture. Conjecture 1 The best response dynamic of ALL-OR-NOTHING converges to a Nash equilibrium for any initial strategy profile, for any number of buyers. |
| Researcher Affiliation | Academia | Simina Brˆanzei Purdue University Aris Filos-Ratsikas Ecole Polytechnique F ed erale de Lausanne |
| Pseudocode | No | The paper describes theoretical concepts and proofs but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code for the methodology, nor does it provide a link to a code repository. |
| Open Datasets | No | The paper mentions "randomly generated profiles" for simulations, but does not refer to a publicly available or open dataset with access information. |
| Dataset Splits | No | The paper describes simulation results using randomly generated profiles, but it does not specify any training, validation, or test dataset splits. |
| Hardware Specification | No | The paper describes theoretical models and simulation results, but it does not provide any specific details about the hardware used for these simulations or experiments. |
| Software Dependencies | No | The paper describes theoretical models and simulation results, but it does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper mentions running simulations with "randomly generated profiles" for specific values of n and m and budget ranges, but it does not provide specific hyperparameters, optimizer settings, or a detailed experimental setup section. |