Libo Zhang 张立博

I received my Ph.D. degree from The University of Auckland in 2026. My research focuses on trustworthy artificial intelligence, reinforcement learning, and multi-agent systems. During my Ph.D., I studied multi-agent coordination. More recently, I have become interested in the reasoning processes of Transformers and the behavior of diffusion models.

I completed my undergraduate studies in Chongqing, a wonderfully three-dimensional city that is well worth visiting. I also worked as a research assistant with the Algorithms and Logic Group at the University of Electronic Science and Technology of China in Chengdu. Chengdu is a welcoming city with a rich cultural atmosphere, and my time there left a lasting impression on me. As for Auckland, New Zealand is a southern island nation with a distinctive Māori culture and breathtaking landscapes. If you ever have the chance, I highly recommend visiting. Finally, I'm glad you found your way to this page. Feel free to email me about anything!

01 / Research Interests

  • Trustworthy Artificial Intelligence
  • Reinforcement Learning
  • Multi-Agent Systems

02 / Experience

  1. 2022–2026

    Ph.D. in Computer Science

    The University of Auckland · Completed September 2026

    Multi-agent system

  2. 2022–2023

    Research Assistant

    Algorithms and Logic Group · University of Electronic Science and Technology of China (UESTC), Chengdu

    Formal method

  3. 2020–2021

    Master of Professional Studies in Data Science

    The University of Auckland · First Class Honours

    Multi-agent RL

  4. 2021

    Graduate Diploma in Science

    The University of Auckland

  5. 2020

    Bachelor's Degree

    Southwest University

03 / Publications

2026

  1. A Constrained Reinforcement Learning Approach for Strict Constraint Task Planning on Lunar Rovers with Uncertain Time and Resource Consumption

    Siyao Lu, Ai Gao, Jiamou Liu, Rui Xu, Libo Zhang, Zhaoyu Li, and Bo Pan.

    Applied Soft Computing, Volume 202, Part A, Article 115750, 2026.

  2. Context-Aware Multi-Agent Coordination: Learning Correlated Equilibria Under Situational Constraints

    Libo Zhang, Zhirui Zeng, Yang Chen, and Jiamou Liu.

    IJCAI 2026.

  3. Situational-Constrained Multi-Agent Coordination through Correlated Equilibria

    Libo Zhang, Zhirui Zeng, Yang Chen, and Jiamou Liu

    Proc. AAMAS 2026.

2025

  1. Stable Reward Learning for Inverse RL via Monotonic Policy Divergence Reduction

    Yang Chen, Menglin Zou, Jiaqi Zhang, Yitan Zhang, Junyi Yang, Gaël Gendron, Libo Zhang, Jiamou Liu, and Michael Witbrock.

    Proc. NeurIPS 2025.

  2. Boundary Matters: Leveraging Structured Text Plots for Long Text Outline Generation

    Yuanchi Ma, Jiamou Liu, Hui He, Libo Zhang, Haoyuan Li, and Zhendong Niu.

    Proc. EMNLP 2025.

  3. Situational-Constrained Sequential Resources Allocation via Reinforcement Learning

    Libo Zhang, Yang Chen, Toru Takisaka, Kaiqi Zhao, Weidong Li, and Jiamou Liu.

    Proc. IJCAI 2025.

2024

  1. Safe reinforcement learning task planning with uncertain duration and resource consumption in limited daytime for lunar rovers

    Siyao Lu, Rui Xu, Ai Gao, Zhaoyu Li, Jiamou Liu, Libo Zhang, Zhijun Zhao, Shengying Zhu, and Yuqiong Li

    Proc. IAF Space Operations Symposium at IAC 2024.

  2. Optimizing Resource Distribution Towards Energy Justice in Resilient Smart Grids

    Libo Zhang, Yuly Wu, Weidong Li, Song Yang, Yang Chen, Kaiqi Zhao, and Jiamou Liu.

    Proc. PKAW 2024.

  3. Epic-Level Text Generation with LLM Through Auto-Prompted Reinforcement Learning

    Qianqian Qi, Lin Ni, Zhongsheng Wang, Libo Zhang, Jiamou Liu, and Michael Witbrock.

    Proc. IJCNN 2024.

  4. Lexicographic Ranking Supermartingales with Lazy Lower Bounds

    Toru Takisaka, Libo Zhang, Changjiang Wang, and Jiamou Liu.

    Proc. CAV 2024.

  5. Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables

    Yang Chen, Xiao Lin, Bo Yan, Libo Zhang, Jiamou Liu, Neset Özkan Tan, and Michael Witbrock.

    Proc. AAAI 2024.

2023

  1. Integrated Private Data Trading Systems for Data Marketplaces

    Weidong Li, Mengxiao Zhang, Libo Zhang, and Jiamou Liu.

    Proc. ECAI 2023.

  2. Learning Density-Based Correlated Equilibria for Markov Games

    Libo Zhang, Yang Chen, Toru Takisaka, Bakhadyr Khoussainov, Michael Witbrock, and Jiamou Liu.

    Proc. AAMAS 2023.

  3. Adversarial Inverse Reinforcement Learning for Mean Field Games

    Yang Chen, Libo Zhang, Jiamou Liu, and Michael Witbrock.

    Proc. AAMAS 2023.

2022

  1. Individual-Level Inverse Reinforcement Learning for Mean Field Games

    Yang Chen, Libo Zhang, Jiamou Liu, and Shuyue Hu.

    Proc. AAMAS 2022.

2018

  1. An agent-based approach to simulate post-earthquake indoor crowd evacuation

    Lin Ni, Vicente Gonzalez, Jiamou Liu, Anass Rahouti, Libo Zhang, and Bun Por Taing.

    Proc. PRIMA 2018.

04 / Contact

EMAIL

lzha797[at]aucklanduni.ac.nz

AUCKLAND ADDRESS

Room 435, Building 903
314–390 Khyber Pass Road
Newmarket, Auckland 1023

05 / Beyond Research

I must be drinking coffee at this current moment.