Game Theory with Simulation of Other Players
Authors: Vojtěch Kovařík, Caspar Oesterheld, Vincent Conitzer
IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | 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 vojta.kovarik@gmail.com, oesterheld@cmu.edu, conitzer@cs.cmu.edu |
| 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. |