Minimax-Optimal Multi-Agent RL in Markov Games With a Generative Model

Authors: Gen Li, Yuejie Chi, Yuting Wei, Yuxin Chen

NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical This is a theoretical work that we do not foresee any potential negative societal impacts.
Researcher Affiliation Academia Gen Li UPenn Yuejie Chi CMU Yuting Wei UPenn Yuxin Chen UPenn
Pseudocode Yes Algorithm 1: Q-FTRL. Algorithm 2: Auxiliary function sampling i, h, πh = {πj,h}j [m] .
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)? [N/A]
Open Datasets No The paper is theoretical and does not involve empirical experiments with datasets. Thus, no training dataset information is provided.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with datasets. Thus, no dataset split information for validation is provided.
Hardware Specification No The paper is theoretical and does not report on experimental hardware. The ethics statement indicates N/A for compute resources.
Software Dependencies No The paper is theoretical and does not report on software dependencies with specific version numbers for experimental reproducibility. The ethics statement indicates N/A for experimental details.
Experiment Setup No The paper is theoretical and does not provide specific experimental setup details such as hyperparameters or training configurations. The ethics statement indicates N/A for training details.