Yuanhanqing Huang
Decision Sciences · Purdue University West Lafayette
Publications
19
Citations
84
Est. group size
~1
Recurring co-author estimate
Active years
7
Publishing since 2020
Yuanhanqing Huang works on game theory and multi-agent decision-making, developing algorithms that let distributed agents (such as networked players or systems) find stable solutions, like Nash equilibria, even when they only have partial information, limited feedback, or delays in communication. Much of the work is mathematical and algorithmic, focusing on proving how quickly and reliably these methods converge, with applications relevant to networked systems and multi-agent control.
Publication output rose sharply from 2020 to a peak in 2023, then dropped off in 2024-2026, suggesting an active but uneven and possibly slowing recent output.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Offline Learning of Decision Functions in Multiplayer Games with Expectation Constraints
IEEE Transactions on Automatic Control · 2026
- Zeroth-Order Learning in Continuous Games via Residual Pseudogradient Estimates
IEEE Transactions on Automatic Control · 2024
- On the Convergence Rates of A Nash Equilibrium Seeking Algorithm in Potential Games with Information Delays
2023
- Zeroth-Order Learning in Continuous Games via Residual Pseudogradient Estimates
arXiv (Cornell University) · 2023
- Bandit Online Learning in Merely Coherent Games with Multi-Point Pseudo-Gradient Estimate
2023
- A Bandit Learning Method for Continuous Games Under Feedback Delays with Residual Pseudo-Gradient Estimate
2023
- A Bandit Learning Method for Continuous Games under Feedback Delays with Residual Pseudo-Gradient Estimate
arXiv (Cornell University) · 2023
- Bandit Online Learning in Merely Coherent Games with Multi-Point Pseudo-Gradient Estimate
arXiv (Cornell University) · 2023
- Global and Local Convergence Analysis of a Bandit Learning Algorithm in Merely Coherent Games
IEEE Open Journal of Control Systems · 2023
- Distributed Computation of Stochastic GNE With Partial Information: An Augmented Best-Response Approach
IEEE Transactions on Control of Network Systems · 2022
- A Distributed Douglas-Rachford Based Algorithm for Stochastic GNE Seeking with Partial Information
2022 American Control Conference (ACC) · 2022
- On the Convergence Rates of A Nash Equilibrium Seeking Algorithm in Potential Games with Information Delays
arXiv (Cornell University) · 2022
- Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters
arXiv (Cornell University) · 2022
- Distributed Solution of GNEP over Networks via the Douglas-Rachford Splitting Method
2021 60th IEEE Conference on Decision and Control (CDC) · 2021
- A Primal Decomposition Approach to Globally Coupled Aggregative Optimization over Networks
2021 60th IEEE Conference on Decision and Control (CDC) · 2021
- arXiv (Cornell University)×8
- IEEE Transactions on Automatic Control×2
- 2021 60th IEEE Conference on Decision and Control (CDC)×2
- Therapeutic Advances in Neurological Disorders×1
- IEEE Transactions on Control of Network Systems×1
- Net Zhang
Decision Sciences · The Ohio State University
- Tianyu Wang
Decision Sciences · The Ohio State University
- Mohammad Pedramfar
Decision Sciences · Purdue University West Lafayette
- Zaiwei Chen
Computer Science · Purdue University West Lafayette
- Tengyu Xu
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile