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..
Game Theory with Simulation of Other Players
Authors: Vojtěch Kovařík, Caspar Oesterheld, Vincent Conitzer
IJCAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we formalize games in which one player can simulate another at a cost. We first derive some basic properties of such games and then prove a number of results for them, including: (1) introducing simulation into generic-payoff normal-form games makes them easier to solve; (2) if the only obstacle to cooperation is a lack of trust in the possibly-simulated agent, simulation enables equilibria that improve the outcome for both agents; and however (3) there are settings where introducing simulation results in strictly worse outcomes for both players. |
| Researcher Affiliation | Academia | Vojtˇech Kovaˇrík , Caspar Oesterheld and Vincent Conitzer Foundations of Cooperative AI Lab (FOCAL), Carnegie Mellon University EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. It focuses on theoretical definitions, properties, and proofs. |
| Open Source Code | No | The paper does not provide any statement about releasing source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not mention the use of any datasets for training or other purposes. |
| Dataset Splits | No | The paper is theoretical and does not mention any training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental setup that would require specific software dependencies or versions. |
| Experiment Setup | No | The paper is theoretical and does not describe any specific experimental setup details, such as hyperparameters or system-level training settings. |