Hierarchical deep reinforcement learning

Results 181 to 190 of about 98,895 (273)

SecuFL-IoT: an adaptive privacy-preserving federated learning framework for anomaly detection in smart industrial networks. [PDF]

Sci Rep
Alqazzaz A.
europepmc +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam +2 more
wiley +1 more source

AI-Driven Energy-Efficient Routing in IoT-Based Wireless Sensor Networks: A Comprehensive Review. [PDF]

Sensors (Basel)
Thakur S, Sarkar NI, Yongchareon S.
europepmc +1 more source

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck +4 more
wiley +1 more source

Analysis and optimization of student learning paths based on CRNN and sequential data. [PDF]

PLoS One
Deng M, Lu L, Wen S.
europepmc +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian +37 more
wiley +1 more source

An integrated tiny-YOLO v3 and Q-iteration framework for stable, energy-efficient autonomous navigation of quadruped robots on AMB82-mini microcontrollers. [PDF]

Sci Rep
Salih FH, Mazinan AH, Modaresi SM.
europepmc +1 more source

From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids

Advanced Intelligent Systems, EarlyView.
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal, Amalesh Gope, Miho Yanagisawa +2 more
wiley +1 more source

Graph attention-based heterogeneous multi-agent deep reinforcement learning for adaptive portfolio optimization. [PDF]

Sci Rep
Zhang B.
europepmc +1 more source

deep reinforcement learning
fos: computer and information sciences
computer science - artificial intelligence

hierarchical reinforcement learning
artificial intelligence cs.ai
computer science - machine learning

reinforcement learning
machine learning cs.lg
portfolio optimization