Shaoping Xiao

Orcid: 0000-0001-9658-7149

According to our database1, Shaoping Xiao authored at least 20 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Model-free reinforcement learning for motion planning of autonomous agents with complex tasks in partially observable environments.
Auton. Agents Multi Agent Syst., June, 2024

Intelligent Agricultural Management Considering N<sub>2</sub>O Emission and Climate Variability with Uncertainties.
CoRR, 2024

Learning-based agricultural management in partially observable environments subject to climate variability.
CoRR, 2024

Model-Free Motion Planning of Complex Tasks Subject to Ethical Constraints.
Proceedings of the Artificial Intelligence in HCI, 2024

2023
Model-based motion planning in POMDPs with temporal logic specifications.
Adv. Robotics, July, 2023

Optimal Probabilistic Motion Planning With Potential Infeasible LTL Constraints.
IEEE Trans. Autom. Control., 2023

Model-free Motion Planning of Autonomous Agents for Complex Tasks in Partially Observable Environments.
CoRR, 2023

2022
Intelligent Traffic Light via Policy-based Deep Reinforcement Learning.
Int. J. Intell. Transp. Syst. Res., 2022

Online Motion Planning With Soft Metric Interval Temporal Logic in Unknown Dynamic Environment.
IEEE Control. Syst. Lett., 2022

2021
Modular Deep Reinforcement Learning for Continuous Motion Planning With Temporal Logic.
IEEE Robotics Autom. Lett., October, 2021

Online Motion Planning with Soft Timed Temporal Logic in Dynamic and Unknown Environment.
CoRR, 2021

Reinforcement Learning Based Temporal Logic Control with Soft Constraints Using Limit-deterministic Generalized Büchi Automata.
CoRR, 2021

Studies of COVID-19 Outbreak Control Using Agent-Based Modeling.
Complex Syst., 2021

Design of controllable Leader-follower Networks via Memetic Algorithms.
Adv. Complex Syst., 2021

Reinforcement Learning Based Temporal Logic Control with Maximum Probabilistic Satisfaction.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
A machine-learning-enhanced hierarchical multiscale method for bridging from molecular dynamics to continua.
Neural Comput. Appl., 2020

Optimal Probabilistic Motion Planning with Partially Infeasible LTL Constraints.
CoRR, 2020

2006
A meshfree particle method with stress points and its applications at the nanoscale.
Int. J. Comput. Sci. Eng., 2006

2005
The Applications of Meshfree Particle Methods at the Nanoscale.
Proceedings of the Computational Science, 2005

A Grid-Based Bridging Domain Multiple-Scale Method for Computational Nanotechnology.
Proceedings of the Computational Science, 2005


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