Non‐Hermitian Topological Lattice Photonics: An Analytic Perspective
This review establishes exact analytical solutions for non‐Hermitian Hatano–Nelson, Su–Schrieffer–Heeger, and generalized Rice–Mele models. We demonstrate non‐Hermitian skin effects via point‐gap topology, hybrid skin‐topological edge states in 2D lattices, and spin‐polarized boundary modes governed by dual bulk‐boundary correspondence.
Shihua Chen +6 more
wiley +1 more source
Enhanced Q learning and deep reinforcement learning for unmanned combat intelligence planning in adversarial environments. [PDF]
Jianhong X, Gongqian L.
europepmc +1 more source
Deep reinforcement learning for time series: playing idealized trading games
Xiang Gao
openalex +2 more sources
Vision‐Assisted Avocado Harvesting with Aerial Bimanual Manipulation
This work outlines the design and implementation of a bimanual aerial robot that employs visual perception and learning to detect, reach, and harvest avocados. A new gripper and fixer arm assembly is used to harvest avocados, while visual perception enables the detection of avocados and estimation of their position and orientation for determining ...
Zhichao Liu +3 more
wiley +1 more source
Resilience driven EV coordination in multiple microgrids using distributed deep reinforcement learning. [PDF]
Wu Y, Cai T, Li X.
europepmc +1 more source
Deep Reinforcement Learning of Marked Temporal Point Processes
Utkarsh Upadhyay +2 more
openalex +2 more sources
Combining a biomimetic soft‐robot with deep‐learning data analytics sheds light on a unique peripheral dynamics seen in the biosonar system of bats: Bats modulate their ultrasonic biosonar signals upon emission as well as reception with variable, yet highly coordinated motion patterns of their noseleaves and pinnae.
Shuxin Zhang +4 more
wiley +1 more source
Coverage Path Planning Using Actor-Critic Deep Reinforcement Learning. [PDF]
Garrido-Castañeda SI +2 more
europepmc +1 more source
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang +5 more
wiley +1 more source
Quantitative analysis of EXAFS data sets using deep reinforcement learning. [PDF]
Jeong ES, Hwang IH, Han SW.
europepmc +1 more source

