reinforcement learning

RoBCtrl: Attacking GNN-Based Social Bot Detectors via Reinforced Manipulation of Bots Control Interaction

Social networks have become a crucial source of real-time information for individuals. The influence of social bots within these platforms has garnered considerable attention from researchers, leading to the development of numerous detection technologies. However, the vulnerability and robustness of these detection met...

Single-Agent Reinforcement Learning Model for Regional Adaptive Traffic Signal Control

Several studies have employed reinforcement learning (RL) to address the challenges of regional adaptive traffic signal control (ATSC) and achieved promising results. In this field, existing research predominantly adopts multi-agent frameworks. However, the adoption of multi-agent frameworks presents challenges for sca...

Physics-constrained multi-agent reinforcement learning within a cognitive digital twin for scalable and cyber-resilient distribution network reconfiguration

A review of full-stack autonomous obstacle avoidance for assistive robots for the disabled

With the intensification of population aging and the increasing awareness of protecting the rights of the disabled, significant progress has been made in assistive robots for visually impaired people, the mobility impairments and other groups. Research in this field focuses on four key technical dimensions: environment...

A framework for benchmarking traffic signal control robustness under incidents: comparative study of reinforcement learning-based methods

T-REX is introduced, an open-source, SUMO-based simulation framework for training and evaluating RL-TSC methods under dynamic, incident scenarios, and shows that while independent value-based and decentralized pressure-based methods offer fast convergence and generalization in stable traffic conditions and homogeneous...

Selective laser melting of LM25 aluminium alloy reinforced with boron carbide and graphite for machine learning based wear prediction and microstructural characterization

The Selective Laser Melting (SLM) is a modern and innovative aluminium alloy metals additive synthesis technique for fabricating lightweight aluminium matrix composites with complex geometries and superior engineering performance. In the present investigation, LM25 aluminium alloy reinforced with boron carbide (B...

Variance‐Guided Evolutionary Reinforcement Learning for Multi‐Objective Energy Scheduling in Dairy Farms

Electricity consumption on dairy farms has a direct impact on operational cost, renewable energy utilisation and load flexibility. Coordinating electric water heating and battery storage under dynamic tariffs, photovoltaic generation and temperature constraints forms a challenging multi‐objective sequential decision‐...

Lessening the shock of defibrillation with machine learning

A reinforcement learning agent trained on numerical simulations of cardiac arrhythmia reduced the amplitude of pulses used to treat cardiac arrhythmias.

Reinforcement Learning With a Low‐Cost Parallel Linkage Gripper for Static and Dynamic Planar In‐Hand Manipulation

Parallel linkage grippers provide a low‐cost and compact alternative to anthropomorphic hands for planar manipulation tasks. However, their closed‐chain kinematics introduce actuator coupling, singularity‐related constraints, and position‐dependent manipulation capability, making closed‐loop control challenging. This w...

Research on Multi-Objective Task Scheduling Optimization and Reinforcement Learning Decision-Making Methods for Edge-Cloud Collaborative Scalable Information Systems

INTRODUCTION: Edge-cloud schedulers must coordinate latency, energy, load balance, and deadline compliance under changing demand while keeping task-arrival and throughput units physically consistent.OBJECTIVE: This study evaluates MORL-ECSO under an auditable, paired-seed simulation protocol and compares it with tuned...

Physics-Informed Deep Reinforcement Learning with Adaptive Action Masking for Secure Second-Level Emergency Scheduling in Energy Networks

With the integration of a high proportion of volatile renewable energy into modern power grids, systems frequently face severe supply-demand imbalances and escalated situational risks under extreme events. Addressing the high-dimensional risks and stringent response timing requirements in real-time markets of new-type...

Implementation of the Iqra’ Method to Improve Qur’an Reading Skills at Rahmah Al-Asri Qur’anic Education Center, Unit 267, Basirih Selatan Subdistrict, Banjarmasin

This study aims to analyze the implementation of the Iqra’ method in improving Qur’anic reading skills among students at TPA Rahmah Al-Asri Unit 267, Basirih Selatan, Banjarmasin, and to examine the supporting and inhibiting factors influencing its implementation. This study employed a qualitative field research approa...