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..
Converging on Common Knowledge
Authors: Dominik Klein, Rasmus Kræmmer Rendsvig
IJCAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper discusses unreliable communication protocols from a topological perspective and asks If the generals may communicate indefinitely, will they then converge to a state of common knowledge? We answer by making precise and showing the following: common knowledge is attainable if, and only if, we do not care about common knowledge. We cast the analysis in a mathematically expressive framework where convergent sequences and limit points are natural inhabitants, allowing us to show when and how unreliable communication converges to a state of common knowledge. |
| Researcher Affiliation | Academia | Dominik Klein1 and Rasmus Kræmmer Rendsvig2 1University of Bamberg and University of Bayreuth 2Center for Information and Bubble Studies, University of Copenhagen |
| Pseudocode | No | No structured pseudocode or algorithm blocks found. |
| Open Source Code | No | No statement or link providing access to source code for the methodology. |
| Open Datasets | No | This paper is theoretical and does not involve datasets or training. |
| Dataset Splits | No | This paper is theoretical and does not involve dataset splits for validation. |
| Hardware Specification | No | This paper is theoretical and does not describe hardware specifications for experiments. |
| Software Dependencies | No | This paper is theoretical and does not describe specific software dependencies with version numbers. |
| Experiment Setup | No | This paper is theoretical and does not provide details about an experimental setup. |