reinforcement learning

GustaveKateb0709/aedes-rl-control-guangzhou: V2.0.0

Code and data: deep reinforcement learning for weekly mosquito-control allocation under an operational capacity ceiling This package reproduces every number, table and figure in the manuscript. Version 2.0.0 extends the original submission with a weekly operational-capacity ceiling, additional algorithms, cross-year va...

Deep reinforcement learning discovers a novel control algorithm for mitigating flow-induced vibrations in underactuated tandem cylinders

Decentralized Multi-Agent Reinforcement Learning for Optimizing Quantum Memory Based Quantum Repeaters

This repository implements a memory-based quantum repeater chain as a Gymnasium and PettingZoo environment, formulated as a multi-agent Partially Observable Markov Decision Process (POMDP). A Multi-Agent Reinforcement Learning (MARL) system based on the Proximal Policy Optimization (PPO) algorithm is trained to dynamic...

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...