Results 21 to 30 of about 731,139 (136)

Hierarchical Reinforcement Learning for Long‐Distance Multi‐Objective Optimization of Heavy‐Haul Trains via Sequential Task Assignment Across Spatial Segments

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This paper proposes a sequential multi‐task collaboration hierarchical reinforcement learning framework for dynamic multi‐objective optimization of long‐distance heavy‐haul train operations. By decomposing the route into segment‐specific subtasks and coordinating sequential policy invocation through a top‐level dynamic programming framework, the ...
Jianhua Wang, Cong Wang, Qingyuan Wang, Yiding Yu, Xiaoyun Feng   +4 more
wiley   +1 more source

Reinforcement Learning in Microgrid Energy Management: Review, Methods and Prospects

IET Smart Grid, Volume 9, Issue 1, January/December 2026.
Extensive comparison of RL and DRL methods has been provided to highlight their application for various energy management systems for microgrid applications. ABSTRACT A rapid integration of distributed energy resources and electrification has increased the need for intelligent energy management in microgrids under grid‐connected and islanded operation.
Muhammad Fahad Zia, Usman Inayat, Muhammad Junaid Anjum, Haris M. Khalid, Sheroze Liaquat   +4 more
wiley   +1 more source

Intraday Optimal Dispatch Method for Power Systems Considering Source‐Load Uncertainty Under Extreme Stagnant and Calm Weather

IET Smart Grid, Volume 9, Issue 1, January/December 2026.
This paper proposes an intraday optimal dispatch method based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm. ABSTRACT Under high‐penetration renewable energy integration, extreme weather events pose significant risks and challenges to power systems.
Wang Ziting, Lu Peng
wiley   +1 more source

Multi‐Intersection Cooperative Control Platform Framework and Empirical Study in Connected and Automated Vehicle Environment: An Engineering Implementation Perspective

Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.
With the acceleration of urbanization and rapid growth of vehicle ownership, traffic congestion has become a critical bottleneck constraining sustainable urban development. Traditional traffic signal control methods struggle to adapt to the complex traffic environment where connected and automated vehicles (CAVs) coexist with conventional vehicles ...
Yizhe Wang, Ruifa Luo, Xiaoguang Yang, Yue Qian, Song Hu, Mohammad Rezwan Habib   +5 more
wiley   +1 more source

Improving the Efficiency of Deep Reinforcement Learning in NetHack Using VAE and Proposing Additional Rewards

International Journal of Computer Games Technology, Volume 2026, Issue 1, 2026.
Deep reinforcement learning (DRL) has been widely used in agent research across various video games, demonstrating its effectiveness. Recently, there has been increasing interest in DRL research in complex environments such as Roguelike games. Among them, the game NetHack has gained research attention.
Yasuhiro Onuki, Yasuyuki Tahara, Akihiko Ohsuga, Yuichi Sei, Deepali   +4 more
wiley   +1 more source

On the Nash Equilibria of a Simple Discounted Duel [PDF]

Operations Research and Decisions
We formulate and study a two-player, duel game as a nonzero-sum discounted stochastic game. Players P1, and P2 are standing in place and, in each turn, one or both may shoot at the other player.
Athanasios Kehagias
doaj  

Joint Planning for Task Scheduling and Task Result Caching in the Fog Using Reinforcement Learning

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
The rapid expansion of the Internet of Things (IoT) has greatly increased the number of sensors operating within cloud–fog environments. As more users generate processing tasks, there is a critical need to deliver swift and efficient responses. To address this challenge, it is essential to develop a task scheduling framework that leverages available ...
Mohammad Hassan Nataj Solhdar, Mehdi Esnaashari, Richard Murray   +2 more
wiley   +1 more source

Real‐Time Tire Tread Identification From Wheel Tracks Using YOLOv11 and Triplet Embedding

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
This paper presents a unified real‐time framework for tire tread identification that integrates tire‐mark detection and tread retrieval into a single end‐to‐end pipeline. Unlike existing studies that directly apply standard YOLO or metric‐learning models, the proposed system introduces three key innovations: (1) a YOLOv11‐based detector customized with
Hoang Tran Manh, Dung Pham Anh, Phat Nguyen Huu, Richard Murray   +3 more
wiley   +1 more source

A Novel QoS‐Aware Service Composition Method for Cloud‐Based Information Systems Based on a Hybrid Deep Learning–Based Algorithm

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
Quality‐aware service integration in cloud computing information infrastructures typically refers to selecting a suitable subset of services out of those available in order to fulfill a user’s request, considering multiple quality of service (QoS) metrics like response time, cost, availability, and reliability constraints.
Haoran Hong, C. Zhao, L. Lin, Richard Murray   +3 more
wiley   +1 more source

A Comprehensive Review of Reinforcement Learning Applications in Health Monitoring of Civil Infrastructures

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
The concept of structural health monitoring (SHM) of civil infrastructure has evolved rapidly with the incorporation of artificial intelligence (AI). Although available literature mainly focuses on supervised and unsupervised learning to detect and classify damages, both are inherently limited in addressing sequential decision‐making, optimization of ...
Ankit Ullegaddi, S. C. Mohan, Mojtaba Mahmoodian, Ricky W. K. Chan, Amir Sidiq, Francesc Pozo   +5 more
wiley   +1 more source