Personal Information
Hello, I am Hongyao Tang. I am a postdoctoral researcher with Professor Glen Berseth, in Robotics and Embodied AI Lab (REAL) at the Université de Montréal and Mila. Prior to this, I obtained my Ph.D. (Master and Bachelor Degree as well) in Deep Reinforcement Learning (DRL) Lab, Tianjin University advised by Professor Jianye Hao, Zhaopeng Meng, and Li Wang.
My research interests lie in unveiling the learning dynamics of Deep Reinforcement Learning (DRL) and realizing new approaches/paradigms for efficient, performant and generalizable agents. Currently, my research focus is Learning under Nonstationarity and Self-supervised Representation Learning in DRL. I am also interested in Meta RL, MARL, Offline RL and Foundation Models for Decision Making.
I have experiences in applying DRL in practical problems like Electronic Design Automation (EDA), Drug Discovery, Online Games and etc. I am very willing to contribute to addressing real-world problems.
Recent Publications & Preprints
PS: Authors with equal contribution are marked by *.
Bridging Evolutionary Algorithms and Reinforcement Learning: A Comprehensive Survey
Pengyi Li, Jianye Hao, Hongyao Tang, Xian Fu, Yan Zheng, Ke Tang
arXiv preprint 2024
| [Paper]
Reining Generalization in Offline Reinforcement Learning via Representation Distinction
Yi Ma, Hongyao Tang (Corresponding Author), Dong Li, Zhaopeng Meng
NeurIPS 2023
| [Paper]
Boosting Off-policy RL with Policy Representation and Policy-extended Value Function Approximator
Min Zhang, Jianye Hao, Hongyao Tang, Yan Zheng
ICML 2023 Workshop on Frontiers4LCD
| [Paper]
RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolution
Pengyi Li, Jianye Hao, Hongyao Tang, Yan Zheng, Xian Fu
ICML 2023
| [Paper]
The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting
Hongyao Tang, Min Zhang, Jianye Hao
arXiv preprint 2023
| [Paper]
ERL-Re^2: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation
Jianye Hao, Pengyi Li, Hongyao Tang, Yan Zheng, Xian Fu, Zhaopeng Meng
ICLR 2023 & DRL Workshop, NeurIPS 2022
| [Paper]
[Code]
Exploration in Deep Reinforcement Learning: From Single-Agent to Multi-Agent Domain
Jianye Hao, Tianpei Yang, Hongyao Tang, Chenjia Bai, Jinyi Liu, Zhaopeng Meng, Peng Liu
IEEE Transactions on Neural Networks and Learning Systems (Accepted in 2023 Jan)
| [Paper]
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes
Min Zhang*, Hongyao Tang*, Jianye Hao, Yan Zheng
DRL Workshop, NeurIPS 2022
| [Paper]
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang
ICML 2022
| [Paper]
[Code]
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Boyan Li*, Hongyao Tang*, Yan Zheng, Jianye Hao, Pengyi Li, Zhen Wang, Zhaopeng Meng, Li Wang
ICLR 2022 & NeurIPS 2021 DRL Workshop Contributed Talk
| [Paper]
What about Inputting Policy in Value Function: Policy Representation and Policy-Extended Value Function Approximator
Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang
AAAI 2022 Oral Presentation (< 5%) & NeurIPS 2020 DRL Workshop
| [Paper]
More Publications
Education & Work (Internship) Experiences
2023.11 - Present
Postdoctoral Researcher, Robotics and Embodied AI Lab (REAL), UdeM/Mila (work with Glen Berseth)
2019.09 - 2023.06
Phd, College of Intelligence and Computing, Tianjin University (advised by Jianye Hao and Zhaopeng Meng)
2020.05 - 2023.04
DRL Researcher (Intern), Noah's Ark Lab, Huawei (work with Chen Chen and Zhentao Tang)
2019.09 - 2020.04
AI Researcher (Intern), Quantum Lab, Tencent (work with Guangyong Chen)
2018.07 - 2018.10
DRL Researcher (Intern), Fuxi AI Lab, NetEase (work with Tangjie Lv)
2017.09 - 2019.07
Master, College of Intelligence and Computing, Tianjin University (advised by Jianye Hao and Li Wang)
2013.09 - 2017.07
Bachelor, School of Software Engineering, Tianjin University
Academic Service
RLC
2024
NeurIPS
2021 - 2023 (Top Reviewer Award at NeurIPS 2022)
ICLR
2022 - 2024 (Highlighted Reviewer Award at ICLR 2022)
ICML
2021 - 2024
AAAI
2021 - 2024
IJCAI
2021 - 2024
AAMAS
2021 - 2024
Transactions on Machine Learning Research (TMLR)
Invited Talks
2022.07 & 2022.06 & 2022.01
Policy-extended Value Function Approximator and Policy Representation in Reinforcement Learning
The 9th China Computer Federation Seminar on Agent and Multi-agent System (2022 Jul)
RL China Community Weakly Seminar (2022 Jun)
The 3rd International Conference on Distributed Artificial Intelligence (2022 Jan)
2022.07
Towards Understanding The Learning Dynamics of Deep Reinforcement Learning
Huawei Noah’s Ark Lab, Decision-making and Reasoning Group (during internship)
2021.10
Self-supervised Reinforcement Learning — A Perspective of Representation
2021 TJU RL Summer Seminar
2021.06
Reward-agnostic Unsupervised State Representation in Deep Reinforcement Learning
Huawei Noah’s Ark Lab, Decision-making and Reasoning Group (during internship)
2020.11
State Abstraction and State Representation Learning in Reinforcement Learning
Huawei Noah’s Ark Lab, Decision-making and Reasoning Group (during internship)
2019.10
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces
The 1st International Conference on Distributed Artificial Intelligence (DAI 2019)
2019.08
Bias and Variance in Deep Reinforcement Learning
2019 TJU RL Summer Seminar