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..
Prevailing in the Dark: Information Walls in Strategic Games
Authors: Pavel Naumov, Wenxuan Zhang5842-5850
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The main technical result is a sound and complete logical system that describes the interplay between the knowledge and the strategic ability modalities. |
| Researcher Affiliation | Academia | 1 University of Southampton, Southampton, United Kingdom 2 Scripps College; Claremont, California, United States |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. It focuses on logical systems and proofs. |
| Open Source Code | No | The paper does not provide concrete access to source code. As a theoretical paper, it describes a logical system and its properties, not an implementation. |
| Open Datasets | No | The paper does not provide concrete access information for a publicly available or open dataset, as it is a theoretical paper focusing on logical systems and proofs, not empirical studies using datasets. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) as it is a theoretical paper and does not involve empirical data splitting for experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running experiments, as it is a theoretical paper and does not involve empirical experiments requiring hardware specifications. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate the experiment, as it is a theoretical paper and does not describe a software implementation for empirical experimentation. |
| Experiment Setup | No | The paper does not contain specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) as it is a theoretical paper and does not describe empirical experiments. |