203 citations · 262 across the 22 of their papers we have counts for
22 papers
Rating-based Reinforcement Learning
Devin White, Mingkang Wu, Ellen Novoseller +3
This paper develops a novel rating-based reinforcement learning approach that uses human ratings to obtain human guidance in reinforcement learning. Different from the existing pre…
Fairness in Preference-based Reinforcement Learning
Umer Siddique, Abhinav Sinha, Yongcan Cao
In this paper, we address the issue of fairness in preference-based reinforcement learning (PbRL) in the presence of multiple objectives. The main objective is to design control po…
Human-guided Robot Behavior Learning: A GAN-assisted Preference-based Reinforcement Learning Approach
Huixin Zhan, Feng Tao, Yongcan Cao
Human demonstrations can provide trustful samples to train reinforcement learning algorithms for robots to learn complex behaviors in real-world environments. However, obtaining su…
Learn to Exceed: Stereo Inverse Reinforcement Learning with Concurrent Policy Optimization
Feng Tao, Yongcan Cao
In this paper, we study the problem of obtaining a control policy that can mimic and then outperform expert demonstrations in Markov decision processes where the reward function is…
Graph Based Multi-layer K-means++ (G-MLKM) for Sensory Pattern Analysis in Constrained Spaces
Feng Tao, Rengan Suresh, Johnathan Votion +1
In this paper, we focus on developing a novel unsupervised machine learning algorithm, named graph based multi-layer k-means++ (G-MLKM), to solve data-target association problem wh…
Deep Model Compression Via Two-Stage Deep Reinforcement Learning
Huixin Zhan, Wei-Ming Lin, Yongcan Cao
Besides accuracy, the model size of convolutional neural networks (CNN) models is another important factor considering limited hardware resources in practical applications. For exa…
Relationship Explainable Multi-objective Optimization Via Vector Value Function Based Reinforcement Learning
Huixin Zhan, Yongcan Cao
Solving multi-objective optimization problems is important in various applications where users are interested in obtaining optimal policies subject to multiple, yet often conflicti…
Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation
Huixin Zhan, Yongcan Cao
Solving multi-objective optimization problems is important in various applications where users are interested in obtaining optimal policies subject to multiple, yet often conflicti…
A Multi-Layer K-means Approach for Multi-Sensor Data Pattern Recognition in Multi-Target Localization
Samuel Silva, Rengan Suresh, Feng Tao +2
Data-target association is an important step in multi-target localization for the intelligent operation of un- manned systems in numerous applications such as search and rescue, tr…
Multi-Objective Cooperative Search of Spatially Diverse Routes in Uncertain Environments
Johnathan Votion, Yongcan Cao
This paper focuses on developing new navigation and reconnaissance capabilities for cooperative unmanned systems in uncertain environments. The goal is to design a cooperative mult…
Multi-Sensor Data Pattern Recognition for Multi-Target Localization: A Machine Learning Approach
Kasthurirengan Suresh, Samuel Silva, Johnathan Votion +1
Data-target pairing is an important step towards multi-target localization for the intelligent operation of unmanned systems. Target localization plays a crucial role in numerous a…
Towards Energy-Efficient Communication Management in the Distributed Control of Networked Cyber-Physical Systems
Yongcan Cao, Eduardo Pasiliao
In this paper, we study the distributed control of networked cyber-physical systems when a much more energy-efficient distributed communication management strategy is proposed to s…
Decentralized Event-Triggered Consensus over Unreliable Communication Networks
Eloy Garcia, Yongcan Cao, David W. Casbeer
This article studies distributed event-triggered consensus over unreliable communication channels. Communication is unreliable in the sense that the broadcast channel from one agen…
Distributed Adaptive Fault-Tolerant Control of Uncertain Multi-Agent Systems
Mohsen Khalili, Xiaodong Zhang, Marios M. Polycarpou +2
This paper presents an adaptive fault-tolerant control (FTC) scheme for a class of nonlinear uncertain multi-agent systems. A local FTC scheme is designed for each agent using loca…
Periodic Event-Triggered Synchronization of Linear Multi-agent Systems with Communication Delays
Eloy Garcia, Yongcan Cao, David W. Casbeer
Multi-agent systems cooperation to achieve global goals is usually limited by sensing, actuation, and communication issues. At the local level, continuous measurement and actuation…
Decentralized Event-Triggered Consensus of Linear Multi-agent Systems under Directed Graphs
Eloy Garcia, Yongcan Cao, Xiaofeng Wang +1
An event-triggered control technique for consensus of multi-agent systems with general linear dynamics is presented. This paper extends previous work to consider agents that are co…
Bridge Consensus: Ignoring Initial Inessentials
David W. Casbeer, Yongcan Cao, Eloy Garcia +1
In this paper, the problem of bridge consensus is presented and solved. Bridge consensus consists of a network of nodes, some of whom are participating and others are non-participa…
UAV Circumnavigating an Unknown Target Under a GPS-denied Environment with Range-only Measurements
Yongcan Cao
One typical application of unmanned aerial vehicles is the intelligence, surveillance, and reconnaissance mission, where the objective is to improve situation awareness through inf…
UAV Circumnavigation of an Unknown Target Without Location Information Using Noisy Range-based Measurements
Araz Hashemi, Yongcan Cao, David Casbeer +1
This paper proposes a control algorithm for a UAV to circumnavigate an unknown target at a fixed radius when the location information of the UAV is unavailable. By assuming that th…
Circumnavigation of an Unknown Target Using UAVs with Range and Range Rate Measurements
Yongcan Cao, Jonathan Muse, David Casbeer +1
This paper presents two control algorithms enabling a UAV to circumnavigate an unknown target using range and range rate (i.e., the derivative of range) measurements. Given a presc…
Finite-time Consensus for Multi-agent Networks with Unknown Inherent Nonlinear Dynamics
Yongcan Cao, Wei Ren
This paper focuses on analyzing the finite-time convergence of a nonlinear consensus algorithm for multi-agent networks with unknown inherent nonlinear dynamics. Due to the existen…
An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination
Yongcan Cao, Wenwu Yu, Wei Ren +1
This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006.…