68 citations · 85 across the 12 of their papers we have counts for
12 papers
MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning
Tianmeng Hu, Biao Luo, Chunhua Yang +1
Deep reinforcement learning (RL) has been applied extensively to solve complex decision-making problems. In many real-world scenarios, tasks often have several conflicting objectiv…
Memristor-Based Selective Convolutional Circuit for High-Density Salt-and-Pepper Noise Removal
Binghui Ding, Ling Chen, Chuandong Li +2
In this article, we propose a memristor-based selective convolutional (MSC) circuit for salt-and-pepper (SAP) noise removal. We implement its algorithm using memristors in analog c…
Ensemble Control for Stochastic Systems with Asymmetric Laplace Noises
Yajie Yu, Xuehui Ma, Shiliang Zhang +4
This paper presents an adaptive ensemble control for stochastic systems subject to asymmetric noises and outliers. Asymmetric noises skew system observations, and outliers with lar…
Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties
Xuehui Ma, Shiliang Zhang, Yushuai Li +2
This paper is concerned with the robust tracking control of linear uncertain systems, whose unknown system parameters and disturbances are bounded within ellipsoidal sets. We propo…
Model-Assisted Probabilistic Safe Adaptive Control With Meta-Bayesian Learning
Shengbo Wang, Ke Li, Yin Yang +3
Breaking safety constraints in control systems can lead to potential risks, resulting in unexpected costs or catastrophic damage. Nevertheless, uncertainty is ubiquitous, even amon…
Optimal Resource Allocation between Two Nonfully Cooperative Wireless Networks under Malicious Attacks: A Gestalt Game Perspective
Yukang Cui, Xinru Yang, Tingwen Huang +1
In this paper, the problem of seeking optimal distributed resource allocation (DRA) policies on cellular networks in the presence of an unknown malicious adding-edge attacker is in…
Resilient Output Consensus Control of Heterogeneous Multi-agent Systems against Byzantine Attacks: A Twin Layer Approach
Xin Gong, Yiwen Liang, Yukang Cui +2
This paper studies the problem of cooperative control of heterogeneous multi-agent systems (MASs) against Byzantine attacks. The agent affected by Byzantine attacks sends different…
Data-Driven Leader-following Consensus for Nonlinear Multi-Agent Systems against Composite Attacks: A Twins Layer Approach
Xin Gong, Jintao Peng, Dong Yang +3
This paper studies the leader-following consensuses of uncertain and nonlinear multi-agent systems against composite attacks (CAs), including Denial of Service (DoS) attacks and ac…
Resilient Output Containment Control of Heterogeneous Multiagent Systems Against Composite Attacks: A Digital Twin Approach
Yukang Cui, Lingbo Cao, Michael V. Basin +3
This paper studies the distributed resilient output containment control of heterogeneous multiagent systems against composite attacks, including denial-of-services (DoS) attacks, f…
Towards Safe and Efficient Swarm-Human Collaboration: A Hierarchical Multi-Agent Pickup and Delivery framework
Xin Gong, Tieniu Wang, Yukang Cui +1
The multi-Agent Pickup and Delivery (MAPD) problem is crucial in the realm of Intelligent Storage Systems (ISSs), where multiple robots are assigned with time-varying, heterogeneou…
Suboptimal Safety-Critical Control for Continuous Systems Using Prediction-Correction Online Optimization
Shengbo Wang, Shiping Wen, Yin Yang +3
This paper investigates the control barrier function (CBF) based safety-critical control for continuous nonlinear control affine systems using the more efficient online algorithms…
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars
Bo Lyu, Shengbo Wang, Shiping Wen +4
The sparse representation of graphs has shown great potential for accelerating the computation of graph applications (e.g., Social Networks, Knowledge Graphs) on traditional comput…