Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry
Authors: Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti5252-5259
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We design a polynomial-time algorithm to compute an optimal ex ante persuasive signaling scheme in symmetric BNCGs with affine cost functions. Our algorithm exploits the ellipsoid method. We first formulate the problem as an LP (Problem (1)) with polynomially many constraints and exponentially many variables. Then, we show how to find an optimal solution to the LP in polynomial time by applying the ellipsoid algorithm to its dual (Problem (2))... |
| Researcher Affiliation | Academia | Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133, Milan, Italy {name.surname}@polimi.it |
| Pseudocode | No | The paper describes algorithms and formulations (e.g., LP formulations, ellipsoid method, min-cost flow problem) in prose and mathematical notation but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statement or link indicating that the source code for their methodology is publicly available. |
| Open Datasets | No | The paper is theoretical and focuses on algorithm design and complexity analysis; it does not use or mention any publicly available datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments with data, thus it does not provide information on dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not conduct empirical experiments, therefore no hardware specifications for running experiments are mentioned. |
| Software Dependencies | No | The paper presents theoretical results and algorithms; it does not describe a software implementation or list specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on algorithm design and complexity analysis, thus it does not provide details about an experimental setup or hyperparameters. |