Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (45)
  • Open Access

    REVIEW

    A Survey of Hybrid Energy-Aware and Decentralized Game-Theoretic Approaches in Intelligent Multi-Robot Task Allocation

    Ali Hamidoğlu1,2, Ali Elghirani3,4, Ömer Melih Gül5,6,7, Seifedine Kadry8,*

    CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.077060 - 09 April 2026

    Abstract Multi-Robot Task Allocation (MRTA) has proven its importance in the current and near-future era, wherein in every aspect of life, there will be robots to handle tasks effectively and efficiently. While there has been a growing interest in MRTA problems in the robotics industry, the question arises of how to make robots more decentralized and intelligent through rational decision-makers rather than ones that are centralized and filled with black boxes. This survey aims to address that question by examining recent MRTA literature and exploring topics including MRTA taxonomy, centralized and decentralized controls, static and dynamic… More >

  • Open Access

    ARTICLE

    A Hybrid CNN-XGBoost Framework for Phishing Email Detection Using Statistical and Semantic Features

    Lin-Hui Liu1, Dong-Jie Liu1,*, Yin-Yan Zhang1, Xiao-Bo Jin2, Xiu-Cheng Wu3, Guang-Gang Geng1

    CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074253 - 12 March 2026

    Abstract Phishing email detection represents a critical research challenge in cybersecurity. To address this, this paper proposes a novel Double-S (statistical-semantic) feature model based on three core entities involved in email communication: the sender, recipient, and email content. We employ strategic game theory to analyze the offensive strategies of phishing attackers and defensive strategies of protectors, extracting statistical features from these entities. We also leverage the Qwen large language model to excavate implicit semantic features (e.g., emotional manipulation and social engineering tactics) from email content. By integrating statistical and semantic features, our model achieves a robust More >

  • Open Access

    REVIEW

    Mapping the Intellectual Structure of Game Theory Applications in Blockchain: A Decade Bibliometric Analysis

    Arvind Panwar1, Urvashi Sugandh2, Achin Jain3,*, Arun Kumar Dubey3, Sarita Yadav3

    Journal of Blockchain and Intelligent Computing, Vol.2, pp. 1-26, 2026, DOI:10.32604/jbic.2026.077106 - 11 March 2026

    Abstract This study conducts a systematic bibliometric investigation of scholarly research on game-theoretic applications in blockchain ecosystems over the period 2014–2024, based on 554 publications retrieved from the Web of Science and Scopus databases. Using citation analysis, co-citation analysis, bibliographic coupling, and keyword co-occurrence mapping implemented through VOSviewer, the study quantitatively reveals the intellectual structure, thematic evolution, and collaborative architecture of this interdisciplinary research domain. The results demonstrate an exponential growth in publications after 2020, corresponding with the rapid expansion of decentralized finance (DeFi) and Web3 ecosystems. Five dominant research clusters are identified: consensus mechanisms, token… More >

  • Open Access

    ARTICLE

    Deep Multi-Agent Stochastic Optimization for Traffic Management in IoT-Enabled Transportation Networks

    Nada Alasbali*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4943-4958, 2025, DOI:10.32604/cmc.2025.068330 - 23 October 2025

    Abstract Intelligent Traffic Management (ITM) has progressively developed into a critical component of modern transportation networks, significantly enhancing traffic flow and reducing congestion in urban environments. This research proposes an enhanced framework that leverages Deep Q-Learning (DQL), Game Theory (GT), and Stochastic Optimization (SO) to tackle the complex dynamics in transportation networks. The DQL component utilizes the distribution of traffic conditions for epsilon-greedy policy formulation and action and choice reward calculation, ensuring resilient decision-making. GT models the interaction between vehicles and intersections through probabilistic distributions of various features to enhance performance. Results demonstrate that the proposed More >

  • Open Access

    ARTICLE

    Cooperative Game Theory-Based Optimal Scheduling Strategy for Microgrid Alliances

    Zhiyuan Zhang1, Meng Shuai2, Bin Wang1, Ying He3, Fan Yang1, Liyan Ren4,*, Yuyuan Zhang4, Ziren Wang4

    Energy Engineering, Vol.122, No.10, pp. 4169-4194, 2025, DOI:10.32604/ee.2025.066793 - 30 September 2025

    Abstract With the rapid development of renewable energy, the Microgrid Coalition (MGC) has become an important approach to improving energy utilization efficiency and economic performance. To address the operational optimization problem in multi-microgrid cooperation, a cooperative game strategy based on the Nash bargaining model is proposed, aiming to enable collaboration among microgrids to maximize overall benefits while considering energy trading and cost optimization. First, each microgrid is regarded as a game participant, and a multi-microgrid cooperative game model based on Nash bargaining theory is constructed, targeting the minimization of total operational cost under constraints such as More >

  • Open Access

    ARTICLE

    Research on Post Evaluation of Mechanized Construction in Power Transmission and Transformation Projects with Game Theory and Fuzzy Grey Projection

    Mingchen Gao*

    Energy Engineering, Vol.122, No.8, pp. 3243-3263, 2025, DOI:10.32604/ee.2025.065957 - 24 July 2025

    Abstract Currently, the international economic situation is becoming increasingly complex, and there is significant downward pressure on the global economy. In recent years, China’s infrastructure sector has experienced rapid growth, with the structure of its power engineering business gradually shifting from traditional infrastructure construction to more diversified areas such as production and operation, as well as emergency repairs. As a result, the transformation of mechanized construction in power transmission and transformation projects has become increasingly urgent. This article proposes a post-evaluation model based on game theory to improve comprehensive weighting and fuzzy grey relational projection sorting,… More > Graphic Abstract

    Research on Post Evaluation of Mechanized Construction in Power Transmission and Transformation Projects with Game Theory and Fuzzy Grey Projection

  • Open Access

    ARTICLE

    Privacy Preserving Federated Anomaly Detection in IoT Edge Computing Using Bayesian Game Reinforcement Learning

    Fatima Asiri1, Wajdan Al Malwi1, Fahad Masood2, Mohammed S. Alshehri3, Tamara Zhukabayeva4, Syed Aziz Shah5, Jawad Ahmad6,*

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3943-3960, 2025, DOI:10.32604/cmc.2025.066498 - 03 July 2025

    Abstract Edge computing (EC) combined with the Internet of Things (IoT) provides a scalable and efficient solution for smart homes. The rapid proliferation of IoT devices poses real-time data processing and security challenges. EC has become a transformative paradigm for addressing these challenges, particularly in intrusion detection and anomaly mitigation. The widespread connectivity of IoT edge networks has exposed them to various security threats, necessitating robust strategies to detect malicious activities. This research presents a privacy-preserving federated anomaly detection framework combined with Bayesian game theory (BGT) and double deep Q-learning (DDQL). The proposed framework integrates BGT… More >

  • Open Access

    ARTICLE

    A Multi-Objective Joint Task Offloading Scheme for Vehicular Edge Computing

    Yiwei Zhang, Xin Cui*, Qinghui Zhao

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2355-2373, 2025, DOI:10.32604/cmc.2025.065430 - 03 July 2025

    Abstract The rapid advance of Connected-Automated Vehicles (CAVs) has led to the emergence of diverse delay-sensitive and energy-constrained vehicular applications. Given the high dynamics of vehicular networks, unmanned aerial vehicles-assisted mobile edge computing (UAV-MEC) has gained attention in providing computing resources to vehicles and optimizing system costs. We model the computing offloading problem as a multi-objective optimization challenge aimed at minimizing both task processing delay and energy consumption. We propose a three-stage hybrid offloading scheme called Dynamic Vehicle Clustering Game-based Multi-objective Whale Optimization Algorithm (DVCG-MWOA) to address this problem. A novel dynamic clustering algorithm is designed… More >

  • Open Access

    ARTICLE

    Multi-Agent Reinforcement Learning for Moving Target Defense Temporal Decision-Making Approach Based on Stackelberg-FlipIt Games

    Rongbo Sun, Jinlong Fei*, Yuefei Zhu, Zhongyu Guo

    CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3765-3786, 2025, DOI:10.32604/cmc.2025.064849 - 03 July 2025

    Abstract Moving Target Defense (MTD) necessitates scientifically effective decision-making methodologies for defensive technology implementation. While most MTD decision studies focus on accurately identifying optimal strategies, the issue of optimal defense timing remains underexplored. Current default approaches—periodic or overly frequent MTD triggers—lead to suboptimal trade-offs among system security, performance, and cost. The timing of MTD strategy activation critically impacts both defensive efficacy and operational overhead, yet existing frameworks inadequately address this temporal dimension. To bridge this gap, this paper proposes a Stackelberg-FlipIt game model that formalizes asymmetric cyber conflicts as alternating control over attack surfaces, thereby capturing More >

  • Open Access

    ARTICLE

    Intelligent Vehicle Lane-Changing Strategy through Polynomial and Game Theory

    Buwei Dang, Huanming Chen*, Heng Zhang, Jixian Wang, Jian Zhou

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2003-2023, 2025, DOI:10.32604/cmc.2025.062653 - 16 April 2025

    Abstract This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments. A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system. These trajectories are evaluated using non-cooperative game theory, considering the interaction between the target vehicle and its surroundings. Models considering safety payoffs, speed payoffs, comfort payoffs, and aggressiveness are formulated to obtain a Nash equilibrium solution. This way, collision avoidance is ensured, and an optimal lane change trajectory is planned. Three game scenarios are discussed, and the More >

Displaying 1-10 on page 1 of 45. Per Page