Yongjiang Zhao, Haoyi Zhong, Chang Cyoon Lim^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 449-471, 2024, DOI:10.32604/cmc.2024.048771

Abstract This paper examines the difficulties of managing distributed power systems, notably due to the increasing use of renewable energy sources, and focuses on voltage control challenges exacerbated by their variable nature in modern power grids. To tackle the unique challenges of voltage control in distributed renewable energy networks, researchers are increasingly turning towards multi-agent reinforcement learning (MARL). However, MARL raises safety concerns due to the unpredictability in agent actions during their exploration phase. This unpredictability can lead to unsafe control measures. To mitigate these safety concerns in MARL-based voltage control, our study introduces a novel approach: Safety-Constrained Multi-Agent Reinforcement Learning… More >

Yong Ma¹, Han Zhao², Kunyin Guo^3,*, Yunni Xia^3,*, Xu Wang⁴, Xianhua Niu⁵, Dongge Zhu⁶, Yumin Dong⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 907-927, 2024, DOI:10.32604/cmes.2024.048759

Abstract Mobile Edge Computing (MEC) is a technology designed for the on-demand provisioning of computing and storage services, strategically positioned close to users. In the MEC environment, frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery, ultimately enhancing the quality of the user experience. However, due to the typical placement of edge devices and nodes at the network’s periphery, these components may face various potential fault tolerance challenges, including network instability, device failures, and resource constraints. Considering the dynamic nature of MEC, making high-quality content caching decisions for real-time mobile applications, especially… More >

Xia Li¹, Zhanyou Ma^1,*, Zhibao Mian², Ziyuan Liu¹, Ruiqi Huang¹, Nana He¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4129-4152, 2024, DOI:10.32604/cmc.2024.047168

Abstract Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications. Although there is an extensive literature on qualitative properties such as safety and liveness, there is still a lack of quantitative and uncertain property verifications for these systems. In uncertain environments, agents must make judicious decisions based on subjective epistemic. To verify epistemic and measurable properties in multi-agent systems, this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge (FCTLK). We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy… More >

Xinci Zhou, Jin Zhu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2705-2727, 2024, DOI:10.32604/cmes.2024.046363

Abstract As the number of automated guided vehicles (AGVs) within automated container terminals (ACT) continues to rise, conflicts have become more frequent. Addressing point and edge conflicts of AGVs, a multi-AGV conflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards. For larger terminal maps and complex environments, the grid method is employed to model AGVs’ road networks. An improved bounded conflict-based search (IBCBS) algorithm tailored to ACT is proposed, leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range. Comparative experiments involving 60… More >

Tianzhe Jiao, Xiaoyue Feng, Chaopeng Guo, Dongqi Wang, Jie Song^*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3585-3603, 2023, DOI:10.32604/cmc.2023.040068

Abstract Mobile-edge computing (MEC) is a promising technology for the fifth-generation (5G) and sixth-generation (6G) architectures, which provides resourceful computing capabilities for Internet of Things (IoT) devices, such as virtual reality, mobile devices, and smart cities. In general, these IoT applications always bring higher energy consumption than traditional applications, which are usually energy-constrained. To provide persistent energy, many references have studied the offloading problem to save energy consumption. However, the dynamic environment dramatically increases the optimization difficulty of the offloading decision. In this paper, we aim to minimize the energy consumption of the entire MEC system under the latency constraint by… More >

Claire Prudhomme¹ , Ana Roxin² , Christophe Cruz² , Frank Boochs¹

Revue Internationale de Géomatique, Vol.30, No.1, pp. 37-65, 2020, DOI:10.3166/rig.2020.00102

Abstract La gestion de catastrophe nécessite une préparation collaborative entre les divers intervenants. Les exercices collaboratifs visent à entraîner les intervenants à appliquer les plans préparés ainsi qu’à identifier les problèmes et points d’améliorations potentiels. Ces exercices étant coûteux, la simulation informatique est un outil permettant d’optimiser la préparation à l’aide d’une plus grande diversité de cas. Cependant, les travaux de recherche centrés sur la simulation et la gestion de catastrophe sont spécialisés sur un problème spécifique plutôt que sur l’optimisation globale des plans préparés. Cette limite s’explique par le défi que constitue la réalisation d’un modèle de simulation capable de… More >

Hélène Mathian¹, Lena Sanders²

Revue Internationale de Géomatique, Vol.31, No.1, pp. 21-45, 2022, DOI:10.3166/RIG31.21-45

Abstract L’objectif de cet article est de comparer une approche statistique, l’analyse des données (AD) et une approche de simulation, les systèmes multi-agents (SMA). Ces deux familles de méthodes sont a priori considérées comme représentatives d’une approche numérique, respectivement symbolique, de la modélisation spatiale. Le cas d’application qui est mobilisé tout au long de l’article est celui de la ségrégation de l’espace scolaire en Île-deFrance. En premier lieu sont explicitées et discutées les différentes étapes menant d’une question thématique à l’opérationnalisation d’une méthodologie d’analyse statistique ou de simulation destinée à analyser cette question. Pour effectuer cette comparaison, on développe un cadre… More >

Hamida Litimein¹, Zhen-You Huang¹, Muhammad Shamrooz Aslam^2,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 321-341, 2023, DOI:10.32604/iasc.2023.036786

Abstract In this paper, we study the circular formation problem for the second-order multi-agent systems in a plane, in which the agents maintain a circular formation based on a probabilistic position. A distributed hybrid control protocol based on a probabilistic position is designed to achieve circular formation stabilization and consensus. In the current framework, the mobile agents follow the following rules: 1) the agent must follow a circular trajectory; 2) all the agents in the same circular trajectory must have the same direction. The formation control objective includes two parts: 1) drive all the agents to the circular formation; 2) avoid… More >

Zhengkai Ding^1,2, Qiming Fu^1,2,*, Jianping Chen^2,3,4,*, You Lu^1,2, Hongjie Wu¹, Nengwei Fang⁴, Bin Xing⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091

Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining occupants’ thermal comfort. MAQMC is divided into MAQMC2 (MAQMC… More >

Shrouk H. Hessen^1,2,*, Hatem M. Abdul-kader¹, Ayman E. Khedr³, Rashed K. Salem¹

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3015-3028, 2023, DOI:10.32604/cmc.2023.033212

Abstract According to the advances in users’ service requirements, physical hardware accessibility, and speed of resource delivery, Cloud Computing (CC) is an essential technology to be used in many fields. Moreover, the Internet of Things (IoT) is employed for more communication flexibility and richness that are required to obtain fruitful services. A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents. This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various utilities and a significant number… More >