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  • Open Access

    ARTICLE

    Optimal Design of Drying Process of the Potatoes with Multi-Agent Reinforced Deep Learning

    Mohammad Yaghoub Abdollahzadeh Jamalabadi*

    Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 511-536, 2024, DOI:10.32604/fhmt.2024.051004

    Abstract Heat and mass transport through evaporation or drying processes occur in many applications such as food processing, pharmaceutical products, solar-driven vapor generation, textile design, and electronic cigarettes. In this paper, the transport of water from a fresh potato considered as a wet porous media with laminar convective dry air fluid flow governed by Darcy’s law in two-dimensional is highlighted. Governing equations of mass conservation, momentum conservation, multiphase fluid flow in porous media, heat transfer, and transport of participating fluids and gases through evaporation from liquid to gaseous phase are solved simultaneously. In this model, the… More >

  • Open Access

    ARTICLE

    Performance Evaluation of Multi-Agent Reinforcement Learning Algorithms

    Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 337-352, 2024, DOI:10.32604/iasc.2024.047017

    Abstract Multi-Agent Reinforcement Learning (MARL) has proven to be successful in cooperative assignments. MARL is used to investigate how autonomous agents with the same interests can connect and act in one team. MARL cooperation scenarios are explored in recreational cooperative augmented reality environments, as well as real-world scenarios in robotics. In this paper, we explore the realm of MARL and its potential applications in cooperative assignments. Our focus is on developing a multi-agent system that can collaborate to attack or defend against enemies and achieve victory with minimal damage. To accomplish this, we utilize the StarCraft… More >

  • Open Access

    ARTICLE

    Safety-Constrained Multi-Agent Reinforcement Learning for Power Quality Control in Distributed Renewable Energy Networks

    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… More >

  • Open Access

    ARTICLE

    A Fault-Tolerant Mobility-Aware Caching Method in Edge Computing

    Yong Ma1, Han Zhao2, Kunyin Guo3,*, Yunni Xia3,*, 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… More >

  • Open Access

    ARTICLE

    Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

    Xia Li1, Zhanyou Ma1,*, 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… More >

  • Open Access

    ARTICLE

    An Improved Bounded Conflict-Based Search for Multi-AGV Pathfinding in Automated Container Terminals

    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 More >

  • Open Access

    ARTICLE

    Multi-Agent Deep Reinforcement Learning for Efficient Computation Offloading in Mobile Edge Computing

    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… More >

  • Open Access

    ARTICLE

    Modélisation sémantique et programmation générative pour une simulation multi-agent dans le contexte de gestion de catastrophe

    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… More >

  • Open Access

    ARTICLE

    Numérique versus symbolique

    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… More >

  • Open Access

    ARTICLE

    Circular Formation Control with Collision Avoidance Based on Probabilistic Position

    Hamida Litimein1, Zhen-You Huang1, Muhammad Shamrooz Aslam2,*

    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 More >

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