Saket Sarin¹, Sunil K. Singh¹, Sudhakar Kumar¹, Shivam Goyal¹, Brij Bhooshan Gupta^2,3,4,8,*, Wadee Alhalabi⁵, Varsha Arya^6,7

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3123-3138, 2024, DOI:10.32604/cmc.2024.051599

Abstract In the rapidly evolving landscape of today’s digital economy, Financial Technology (Fintech) emerges as a transformative force, propelled by the dynamic synergy between Artificial Intelligence (AI) and Algorithmic Trading. Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning (MARL) and Explainable AI (XAI) within Fintech, aiming to refine Algorithmic Trading strategies. Through meticulous examination, we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm, employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions. These AI-infused Fintech platforms harness collective intelligence More >

Tengda Li, Gang Wang, Qiang Fu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2559-2586, 2024, DOI:10.32604/cmes.2024.052039

Abstract Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation (DTA) and high-dimensional decision space with single agent, this paper combines the deep reinforcement learning (DRL) theory and an improved Multi-Agent Deep Deterministic Policy Gradient (MADDPG-D2) algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA. The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, and considers the introduction of a double noise mechanism to increase the action exploration… More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >

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 >

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 >

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 >

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… 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… 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 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… More >