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 [1].
Pure Nash Equilibria in Resource Graph Games
Authors: Tobias Harks, Max Klimm, Jannik Matuschke
JAIR 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper studies the existence of pure Nash equilibria in resource graph games, a general class of strategic games succinctly representing the players private costs. These games are defined relative to a finite set of resources and the strategy set of each player corresponds to a set of subsets of resources. The cost of a resource is an arbitrary function of the load vector of a certain subset of resources. As our main result, we give complete characterizations of the cost functions guaranteeing the existence of pure Nash equilibria for weighted and unweighted players, respectively. ... We further discuss the computational complexity of pure Nash equilibria in resource graph games... |
| Researcher Affiliation | Academia | Tobias Harks EMAIL Augsburg University, Universit atsstraße 14 86159 Augsburg, Germany Max Klimm EMAIL Technische Universit at Berlin, Straße des 17. Juni 136 10623 Berlin, Germany Jannik Matuschke EMAIL KU Leuven, Research Center for Operations Management Naamsestraat 69, 3000 Leuven, Belgium |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. It primarily focuses on theoretical analysis, mathematical proofs, and characterizations of cost functions in game theory. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code, nor does it include links to a code repository or mention code in supplementary materials. |
| Open Datasets | No | The paper relies on theoretical models and illustrative examples (e.g., Example 1, 2) rather than empirical evaluation using specific datasets. There is no mention of publicly available or open datasets with access information. |
| Dataset Splits | No | The paper does not describe any experiments that would require dataset splits. It focuses on theoretical characterizations and computational complexity within game theory. |
| Hardware Specification | No | The paper is theoretical in nature and does not describe any computational experiments requiring specific hardware. Therefore, no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software or library dependencies with version numbers that would be needed to reproduce experiments. |
| Experiment Setup | No | The paper focuses on theoretical characterizations and computational complexity and does not describe any experimental setup, hyperparameters, or training configurations. |