Polynomial-Time Optimal Equilibria with a Mediator in Extensive-Form Games
Authors: Brian Zhang, Tuomas Sandholm
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We back up our theoretical claims with experiments on a suite of standard benchmark games. ... We ran our algorithm for communication and full-certiļ¬cation equilibria on various two-player games, and compared the results to those given by notions of optimal correlation in games. |
| Researcher Affiliation | Collaboration | Brian Hu Zhang Computer Science Department Carnegie Mellon University bhzhang@cs.cmu.edu Tuomas Sandholm Computer Science Department, CMU Strategic Machine, Inc. Strategy Robot, Inc. Optimized Markets, Inc. sandholm@cs.cmu.edu |
| Pseudocode | No | The paper describes the construction of the mediator-augmented game and refers to solving a linear program but does not provide pseudocode or an algorithm block. |
| Open Source Code | No | Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [No] |
| Open Datasets | Yes | We ran our algorithm for communication and full-certiļ¬cation equilibria on various two-player games... The games used in the experiments are given in Appendix D. All experiments were allocated four CPU cores and 64 GB of RAM. |
| Dataset Splits | No | The paper does not specify any training, validation, or test dataset splits. |
| Hardware Specification | Yes | All experiments were allocated four CPU cores and 64 GB of RAM. |
| Software Dependencies | Yes | Linear programs were solved with Gurobi 9.5. |
| Experiment Setup | Yes | When payments are used, the allowable payment range is [0, M] where M is the reward range of the game. |