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..
Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem
Authors: Fivos Kalogiannis, Jingming Yan, Ioannis Panageas
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Question: Does the paper conduct EMPIRICAL STUDIES WITH DATA ANALYSIS (experiments, dataset evaluation, performance metrics, or hypothesis validation) rather than purely theoretical work? Answer: [No] Justification: The paper is theoretical in nature and does not include experiments. |
| Researcher Affiliation | Academia | Fivos Kalogiannis University of California, Irvine Archimedes/Athena RC, Greece Jingming Yan University of California, Irvine Ioannis Panageas University of California, Irvine Archimedes/Athena RC, Greece |
| Pseudocode | Yes | Algorithm 1 Independent Stochastic Policy-Nested-Gradient (ISPNG) Algorithm 2 Visitation-Regularized Policy Gradient Algorithm (VIS-REG-PG) |
| Open Source Code | No | The paper does not include experiments requiring code. |
| Open Datasets | No | The paper does not include experiments, so it does not discuss training datasets or their public availability. |
| Dataset Splits | No | The paper does not include experiments, so it does not discuss training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not include experiments, so no hardware specifications are mentioned. |
| Software Dependencies | No | The paper does not include experiments, so no specific software dependencies with version numbers are listed. |
| Experiment Setup | No | The paper does not include experiments, so it does not detail specific experimental setup, hyperparameters, or training configurations. |