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..
Nash Equilibria and Their Elimination in Resource Games
Authors: Nicolas Troquard
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce a class of resource games where resources and preferences are described with the language of a resource-sensitive logic. We present two decision problems, the first of which is deciding whether an action profile is a Nash equilibrium. ... This will offer a variety of complexity results that are applicable to a large number of settings. |
| Researcher Affiliation | Academia | Nicolas Troquard Univ. Paris-Est Créteil, LACL EMAIL |
| Pseudocode | Yes | Algorithm 1 Naïve algorithm for NE |
| Open Source Code | No | The paper does not contain any statements about releasing source code or provide links to any code repositories. |
| Open Datasets | No | This paper is theoretical and focuses on formal definitions and complexity analysis of resource games, without involving any empirical data or datasets. |
| Dataset Splits | No | As a theoretical paper, it does not involve empirical experiments or dataset splits for training, validation, or testing. |
| Hardware Specification | No | This paper is theoretical and does not involve empirical experiments that would require hardware specification. |
| Software Dependencies | No | The paper discusses logical frameworks like Linear Logic but does not list any specific software dependencies or their version numbers required to replicate experimental setups. |
| Experiment Setup | No | This paper is theoretical and does not describe an experimental setup with specific hyperparameters or training settings. |