Challenges and opportunities in bioimage analysis

X Li, Y Zhang, J Wu, Q Dai - Nature methods, 2023 - nature.com
Advanced imaging techniques provide holistic observations of complicated biological
phenomena across multiple scales while posing great challenges to data analysis. We …

Spatial planning of urban communities via deep reinforcement learning

Y Zheng, Y Lin, L Zhao, T Wu, D **, Y Li - Nature Computational …, 2023 - nature.com
Effective spatial planning of urban communities plays a critical role in the sustainable
development of cities. Despite the convenience brought by geographic information systems …

Reinforcement Learning Algorithms and Applications in Healthcare and Robotics: A Comprehensive and Systematic Review

MNA Al-Hamadani, MA Fadhel, L Alzubaidi, B Harangi - Sensors, 2024 - mdpi.com
Reinforcement learning (RL) has emerged as a dynamic and transformative paradigm in
artificial intelligence, offering the promise of intelligent decision-making in complex and …

Optimization of high-speed fixed-wing UAV penetration strategy based on deep reinforcement learning

X Zhuang, D Li, Y Wang, X Liu, H Li - Aerospace Science and Technology, 2024 - Elsevier
The penetration decision of unmanned aerial vehicles (UAVs) is one of the key components
for UAVs to detect or strike crucial targets in adversarial environments. Presently, most …

A hierarchical deep reinforcement learning model with expert prior knowledge for intelligent penetration testing

Q Li, M Zhang, Y Shen, R Wang, M Hu, Y Li, H Hao - Computers & Security, 2023 - Elsevier
Penetration testing (PT) is an effective method to assess the security of a network, mainly
carried out by experienced human experts, and is widely applied in practice. It is urgent to …

Co-evolutionary digital twins: A multidimensional dynamic approach to digital engineering

X Tong, J Bao, F Tao - Advanced Engineering Informatics, 2024 - Elsevier
Digital Engineering (DE) must be able to maximize efficiency and update dynamically in
order to keep up with the wave of global interconnection. The evolution of the Digital Twin …

Comparison between phase-field model and coarse-grained model for characterizing cell-resolved morphological and mechanical properties in a multicellular system

G Guan, X Kuang, C Tang, L Zhang - Communications in Nonlinear …, 2023 - Elsevier
Embryonic development is a precise and complex process involving the cell morphology
and mechanics interacting in space and time. The difficulty in quantitatively acquiring …

Intelligent Decision‐Making System of Air Defense Resource Allocation via Hierarchical Reinforcement Learning

M Zhao, G Wang, Q Fu, W Quan, Q Wen… - … Journal of Intelligent …, 2024 - Wiley Online Library
Intelligent decision‐making in air defense operations has attracted wide attention from
researchers. Facing complex battlefield environments, existing decision‐making algorithms …

Targets capture by distributed active swarms via bio-inspired reinforcement learning

K Xu, Y Li, J Sun, S Du, X Di, Y Yang, B Li - Science China Physics …, 2025 - Springer
Natural swarms arranged from cells to herds are usually decentralized but display intriguing
collective intelligence in coordinating individuals across large scales to efficiently achieve …

[HTML][HTML] Delineating the mechanisms and design principles of Caenorhabditis elegans embryogenesis using in toto high-resolution imaging data and computational …

G Guan, Z Zhao, C Tang - Computational and Structural Biotechnology …, 2022 - Elsevier
The nematode (roundworm) Caenorhabditis elegans is one of the most popular animal
models for the study of developmental biology, as its invariant development and transparent …