activity
20232026
most citedDistributed Partial Quantum Consensus of Qubit Networks with Connected Topologies

6 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures

Zixiang Wang, Mengjia Gong, Qiyu Sun +5

With the rapid advancement of artificial intelligence, multi-agent systems (MASs) are evolving from classical paradigms toward architectures built upon large foundation models (LFM…

eess.SY2025

Reinforcement Learning based Constrained Optimal Control: an Interpretable Reward Design

Jingjie Ni, Fangfei Li, Xin Jin +2

This paper presents an interpretable reward design framework for reinforcement learning based constrained optimal control problems with state and terminal constraints. The problem…

cs.MA2024

Distributed Task Allocation for Multi-Agent Systems: A Submodular Optimization Approach

Jing Liu, Fangfei Li, Xin Jin +1

This paper addresses dynamic task allocation in resource-constrained multi-agent systems (MASs) with sequentially updated assignments. We develop a submodular maximization framewor…

quant-ph20246 cited

Distributed Partial Quantum Consensus of Qubit Networks with Connected Topologies

Xin Jin, Zhu Cao, Yang Tang +1

In this paper, we consider the partial quantum consensus problem of a qubit network in a distributed view. The local quantum operation is designed based on the Hamiltonian by using…

cs.RO2023

Motion Planning and Control of A Morphing Quadrotor in Restricted Scenarios

Guiyang Cui, Ruihao Xia, Xin Jin +1

Morphing quadrotors with four external actuators can adapt to different restricted scenarios by changing their geometric structure. However, previous works mainly focus on the impr…

cs.RO2023

Trajectory Planning and Tracking of Hybrid Flying-Crawling Quadrotors

Dongnan Hu, Ruihao Xia, Xin Jin +1

Hybrid Flying-Crawling Quadrotors (HyFCQs) are transformable robots with the ability of terrestrial and aerial hybrid motion. This article presents a trajectory planning and tracki…