3 citations · 11 across the 6 of their papers we have counts for
7 papers
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…
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…
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…