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Search Results (109)
  • 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 the circular formation; 2) avoid… More >

  • Open Access

    ARTICLE

    Coordinated Scheduling of Two-Agent Production and Transportation Based on Non-Cooperative Game

    Ke Xu1,2, Peng Liu1,*, Hua Gong1,2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3279-3294, 2023, DOI:10.32604/iasc.2023.036007

    Abstract A two-agent production and transportation coordinated scheduling problem in a single-machine environment is suggested to compete for one machine from different downstream production links or various consumers. The jobs of two agents compete for the processing position on a machine, and after the processed, they compete for the transport position on a transport vehicle to be transported to two agents. The two agents have different objective functions. The objective function of the first agent is the sum of the makespan and the total transportation time, whereas the objective function of the second agent is the sum of the total completion… More >

  • Open Access

    ARTICLE

    A Proposed Architecture for Local-Host and AWS with Multiagent System

    Jaspreet Chawla1,*, Anil Kr Ahlawat2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2787-2802, 2023, DOI:10.32604/iasc.2023.034775

    Abstract Cloud computing has become one of the leading technologies in the world today. The benefits of cloud computing affect end users directly. There are several cloud computing frameworks, and each has ways of monitoring and providing resources. Cloud computing eliminates customer requirements such as expensive system configuration and massive infrastructure while improving dependability and scalability. From the user’s perspective, cloud computing makes it easy to upload multiagents and operate on different web services. In this paper, the authors used a restful web service and an agent system to discuss, deployments, and analysis of load performance parameters like memory use, central… More >

  • Open Access

    ARTICLE

    Adaptive Cyber Defense Technique Based on Multiagent Reinforcement Learning Strategies

    Adel Alshamrani1,*, Abdullah Alshahrani2

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2757-2771, 2023, DOI:10.32604/iasc.2023.032835

    Abstract The static nature of cyber defense systems gives attackers a sufficient amount of time to explore and further exploit the vulnerabilities of information technology systems. In this paper, we investigate a problem where multiagent systems sensing and acting in an environment contribute to adaptive cyber defense. We present a learning strategy that enables multiple agents to learn optimal policies using multiagent reinforcement learning (MARL). Our proposed approach is inspired by the multiarmed bandits (MAB) learning technique for multiple agents to cooperate in decision making or to work independently. We study a MAB approach in which defenders visit a system multiple… More >

  • Open Access

    ARTICLE

    MAQMC: Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control

    Zhengkai Ding1,2, Qiming Fu1,2,*, Jianping Chen2,3,4,*, You Lu1,2, 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 >

  • Open Access

    REVIEW

    A comprehensive analysis of the role of molecular docking in the development of anticancer agents against the cell cycle CDK enzyme

    PRIYANKA SOLANKI1, NISARG RANA1, PRAKASH C. JHA2, ANU MANHAS1,*

    BIOCELL, Vol.47, No.4, pp. 707-729, 2023, DOI:10.32604/biocell.2023.026615

    Abstract Cancer is considered one of the most lethal diseases responsible for causing deaths worldwide. Although there have been many breakthroughs in anticancer development, cancer remains the major cause of death globally. In this regard, targeting cancer-causing enzymes is one of the efficient therapeutic strategies. Biological functions like cell cycle, transcription, metabolism, apoptosis, and other depend primarily on cyclin-dependent kinases (CDKs). These enzymes help in the replication of DNA in the normal cell cycle process, and deregulation in the functioning of any CDK can cause abnormal cell growth, which leads to cancer. This review is focused on anticancer drug discovery against… More >

  • Open Access

    ARTICLE

    Performance Analysis of a Profile Control Agent for Waste Drilling Fluid Treatment

    Xueyu Zhao*

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.7, pp. 1897-1905, 2023, DOI:10.32604/fdmp.2023.025247

    Abstract A method for the treatment of hazardous waste drilling fluids, potentially leading to environmental pollution, is considered. The waste drilling fluid is treated with an inorganic flocculant, an organic flocculant, and a pH regulator. The profile control agent consists of partially hydrolyzed polyacrylamide, formaldehyde, hexamethylenetetramine, resorcinol, phenol, and the treated waste drilling fluid itself. For a waste drilling fluid concentration of 2500 mg/L, the gelling time of the profile control agent is 25 h, and the gelling strength is 32,000 mPa.s. Compared with the profile control agent prepared by recirculated water under the same conditions, the present profile control agent displays better… More >

  • Open Access

    ARTICLE

    Nanolignin, a Coupling Bio-Agent for Wood-Plastic Composites

    Hamed Younesi-Kordkheili1,*, Antonio Pizzi2,*

    Journal of Renewable Materials, Vol.11, No.5, pp. 2075-2083, 2023, DOI:10.32604/jrm.2023.026706

    Abstract The influence of nanolignin coupling bio-agent on some characteristics of polypropylene-wood flour composites was studied. Thus, nanolignin was prepared by the acidic method, and then different ratios of it (0, 1, 3 and 5 wt%) were added to a polypropylene-wood flour mixture. After mechanically mixing wood flour, nanolignin, and polypropylene, the mixture was injection molded. ASTM methods were used to measure the structural properties of nanolignin, and prepared composites’ water absorption, thickness swelling, bending modulus, and bending, tensile and impact strengths. Transforming the original lignin to nanolignin did not change the chemical bonds of the material. The addition of nanolignin… More >

  • Open Access

    ARTICLE

    Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

    R. Sujatha1,*, T. Abirami2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1775-1787, 2023, DOI:10.32604/csse.2023.031552

    Abstract The digital technologies that run based on users’ content provide a platform for users to help air their opinions on various aspects of a particular subject or product. The recommendation agents play a crucial role in personalizing the needs of individual users. Therefore, it is essential to improve the user experience. The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites. In Context-Aware Recommender Systems (CARS), several influential and contextual variables are identified to provide an effective recommendation. A substantial trade-off is applied in… More >

  • Open Access

    REVIEW

    Artificial Intelligence-Enabled Chatbots in Mental Health: A Systematic Review

    Batyrkhan Omarov1,*, Sergazi Narynov2, Zhandos Zhumanov2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5105-5122, 2023, DOI:10.32604/cmc.2023.034655

    Abstract Clinical applications of Artificial Intelligence (AI) for mental health care have experienced a meteoric rise in the past few years. AI-enabled chatbot software and applications have been administering significant medical treatments that were previously only available from experienced and competent healthcare professionals. Such initiatives, which range from “virtual psychiatrists” to “social robots” in mental health, strive to improve nursing performance and cost management, as well as meeting the mental health needs of vulnerable and underserved populations. Nevertheless, there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare practitioners… More >

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