Civilised Agent Lab
Runchen Xu

Runchen Xu

PhD Student

School of Computer Science, University of Auckland

PhD student studying decentralized AI systems, multi-agent interaction, and mechanism design.

Research Interests

Decentralized Artificial Intelligence
Multi-Agent AI Systems
AI Marketplace Design
Game Theory
Research Profile

About

Previously, I completed my Master's degree in Computer Technology at the University of Electronic Science and Technology of China (UESTC) in 2025. I also earned my Bachelor's degree from UESTC in 2022.

My research primarily focuses on two areas: analyzing and optimizing interactions in multi-agent AI systems, and designing effective mechanisms for the AI marketplace. I am also interested in mobile computing, wireless communications, and networking.

For a full academic record, please see my CV.

Recent Activity

News

Research Archive

Publications

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2026

Mechanism Design for a Sustainable Federated Session Recommender System

Runchen Xu, Mengxiao Zhang, Jiamou Liu

ECML PKDD 2026

A mechanism-design approach for sustainable federated session-based recommender systems.

2025

Contract-based Incentive Mechanism for AI-Generated Content Services in Vehicle Edge Computing

Runchen Xu, Lu Yu, Zheng Chang

Conference Proceedings 2025

A contract-theoretic incentive mechanism for AI-generated content services in vehicle edge computing.

2024

Energy-Efficient Joint Optimization of Sensing and Computation in MEC-assisted IoT Using Mean-Field Game

Runchen Xu, Zheng Chang, Zhu Han, Sahil Garg, Georges Kaddoum, Joel J. P. C. Rodrigues

IEEE Internet of Things Journal 2024

Joint optimization of sensing and computation in MEC-assisted IoT systems using mean-field game theory.

2024

Blockchain-Based Resource Trading in Multi-UAV Edge Computing System

Runchen Xu, Zheng Chang, Xinran Zhang, Timo H"am"al"ainen

IEEE Internet of Things Journal 2024

A blockchain-enabled resource trading framework for multi-UAV edge computing systems.

2023

Contract-Based Incentive Mechanism for Blockchain-Enabled Federated Learning in Vehicle Edge Computing

Runchen Xu, Zheng Chang, Zhiwei Zhao, Geyong Min

IEEE Global Communications Conference 2023

A contract-based incentive framework for blockchain-enabled federated learning in vehicle edge computing.