reinforcement learning

Design and development of an endoscopic robotic system and deep reinforcement learning path planning algorithm for fine-needle biopsy of liver lesions

Abstract This paper presents the design, development and evaluation of a novel robotic platform for endoscopic ultrasound-guided fine-needle biopsy of liver lesions. The system combines a four degrees-of-freedom (DoF) two-segment tendon-driven continuum robot (TDCR) endoscope with a two DoF superelastic nickel–titanium...

Trustworthy Reinforcement Learning for AI-Driven Urban Decision-Making: Sustainable Dynamic Pricing and Resource Optimization for Smart City Operations

Reinforcement learning can support sustainable and resilient urban decision-making when optimization objectives are combined with trustworthy AI principles, and the proposed framework provides a practical basis for accountable AI-based decision-support systems in smart city operations.

Cpu scheduling from classical heuristics to learning-based and multicore paradigms: a systematic review, comparative analysis, and research roadmap

Comparative Finite Element Modal Analysis of Reinforced Concrete Cantilever Beams with Four- and Six-Bar Longitudinal Reinforcement Layouts

This study compares the elastic modal characteristics of reinforced-concrete cantilever beams containing four and six 12 mm longitudinal reinforcing bars using three-dimensional finite element analysis (FEA) and an exploratory machine learning (ML) exercise. Beam geometry, material properties, bond assumptions, and bou...

Cholinergic-dependent dopamine signals in mouse dorsomedial striatum are regulated by frontal but not sensory cortices

Everyday decisions depend on associations between sensory stimuli, actions, and outcomes. The striatum supports these sensorimotor associations through dopamine-dependent plasticity. Recent work has characterized a local striatal microcircuit in which cholinergic interneurons (CINs) modulate dopamine release via activa...

Correction to “Research on autonomous decision‐making method for spacecraft in the mission of rendezvous and approaching to maneuvering target based on deep reinforcement learning”

C. Huang, A. Xing, Q. Zeng, and F. Xiong, Research on autonomous decision-making method for spacecraft in the mission of rendezvous and approaching to maneuvering target based on deep reinforcement learning, Asian J. Control 27 (2025), 2541–2557, DOI https://doi.org/10.1002/asjc.3599. In the Funding section, the fundin...

Dynamic Hippocampal–Striatal Information Flow Accompanies Behavioral Strategy Transitions During Sequential Learning in Pigeons: A Preliminary Study

Preliminary findings suggest that learning is accompanied by frequency-specific changes in brain communication and provide new insights into the neural basis of adaptive decision-making in birds.

IC-VTP: An intent-conditioned reinforcement learning method for robust long-term trajectory prediction of non-cooperative vessels

Harnessing Artificial Intelligence for Strategic Retail Promotions

The retail industry is undergoing a transformation due to the integration of Artificial Intelligence (AI) in promotional strategies. Traditional methods like print ads, radio commercials, and in-store displays face challenges in today's dynamic retail environment, such as the inability to integrate with online platform...

Comparison of Reinforcement Learning-based Algorithm for Eco-Driving Control in Electric Vehicles

A Reinforcement-Learning-Based Fuzzy PID Control Strategy for the Unwinding Tension System of a Lithium-Ion Battery Coating Machine

Stable tension is critical for the coating quality of lithium-ion battery electrodes. As the origin of tension control, the unwinding system’s control accuracy governs the stability of downstream processes and the final yield. To achieve the required precision, we propose a control strategy that combines reinforcement...

Deep reinforcement learning based trajectory optimization in unmanned aerial vehicles: a lyapunov control perspective