Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Constrained Pure Nash Equilibria in Polymatrix Games
Authors: Sunil Simon, Dominik Wojtczak
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the problem of checking for the existence of constrained pure Nash equilibria in a subclass of polymatrix games defined on weighted directed graphs... We identify the most natural tractable cases and show NP or co NP-completness of these problems already for unweighted DAGs. (from Abstract) Additionally, the paper includes structured algorithms such as "Algorithm 1: Algorithm for NE for graphs with two colours and monochromatic queries." |
| Researcher Affiliation | Academia | Sunil Simon IIT Kanpur Kanpur, India Dominik Wojtczak University of Liverpool Liverpool, U.K. |
| Pseudocode | Yes | Algorithm 1: Algorithm for NE for graphs with two colours and monochromatic queries. Algorithm 2: Algorithm for NE on graphs with two colours and monochromatic queries. Algorithm 3: NE on a simple cycle Algorithm 4: NE on a simple cycle Algorithm 5: Algorithm for NE on unweighted DAGs with out-degree 1. Algorithm 6: Algorithm for NE on unweighted DAGs with out-degree 1. |
| Open Source Code | No | The paper does not provide any links to open-source code or explicitly state that code for the described methodology is publicly available. |
| Open Datasets | No | This paper is theoretical and does not involve the use of datasets for training or evaluation. Therefore, no information about public dataset availability is provided. |
| Dataset Splits | No | This paper is theoretical and does not involve empirical experiments with datasets, thus no information on training, validation, or test splits is provided. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used, as it focuses on theoretical analysis and algorithm design without empirical experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers required to reproduce the work. |
| Experiment Setup | No | This paper is theoretical and does not describe an experimental setup with hyperparameters or system-level training settings. |