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Journal articles on the topic 'Multi-Agent-System'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 January 2025

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1

Jemal, Hanen, Zied Kechaou, Mounir Ben Ayed, and Adel M. Alimi. "A Multi Agent System for Hospital Organization." International Journal of Machine Learning and Computing 5, no. 1 (February 2015): 51–56. http://dx.doi.org/10.7763/ijmlc.2015.v5.482.

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2

Myint, Moe Myint. "Useful and Effectiveness of Multi-Agent System." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 671–73. http://dx.doi.org/10.31142/ijtsrd23036.

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3

Elaggoune, Zakarya, Ramdane Maamri, and Imane Boussebough. "The Multi-Agent System Solutions for Big Multi-sensor Data Management." Journal of Ubiquitous Systems and Pervasive Networks 11, no. 2 (June 10, 2019): 23–29. http://dx.doi.org/10.5383/juspn.11.02.004.

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4

K., Gandhimathi, Yogarani A., Sr J. Arockia Jaya, and Ponmathi M. "Mathematical Tutorial System (MTS) Using Fuzzy Logic and Multi-Agent System." International Journal of Innovative Research in Engineering & Management 04, no. 02 (March 2017): 610–14. http://dx.doi.org/10.21276/ijirem.2017.4.2.1.

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Lazrag, Mohamed. "A Multi-agent Architecture for an Intelligent Tutoring System." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 997–1000. http://dx.doi.org/10.5373/jardcs/v12sp4/20201572.

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6

Patel, Rakesh B. "Multi-Agent System: A Recent Trend in Control Engineering." International Journal of Scientific Research 3, no. 7 (June 1, 2012): 180–83. http://dx.doi.org/10.15373/22778179/july2014/57.

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7

Jang, In-Hun, and Kwee-Bo Sim. "Multi Agent System (MAS) Framework for Home Network Application." Journal of Korean Institute of Intelligent Systems 17, no. 1 (February 25, 2007): 80–85. http://dx.doi.org/10.5391/jkiis.2007.17.1.080.

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8

Lozano Murciego, Álvaro, Gabriel Villarrubia González, Alberto López Barriuso, Daniel Hernández De La Iglesia, and Jorge Revuelta Herrero. "Multi agent gathering waste system." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 4, no. 4 (December 22, 2015): 9–22. http://dx.doi.org/10.14201/adcaij201544922.

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Along this paper, we present a new multi agent-based system to gather waste on cities and villages. We have developed a low cost wireless sensor prototype to measure the volume level of the containers. Furthermore a route system is developed to optimize the routes of the trucks and a mobile application has been developed to help drivers in their working days. In order to evaluate and validate the proposed system a practical case study in a real city environment is modeled using open data available and with the purpose of identifying limitations of the system.

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9

Gawande, Prashant. "AI Multi Agent Shopping System." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 10, 2021): 424–25. http://dx.doi.org/10.22214/ijraset.2021.34934.

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The aim of "Ai multi agent Shopping system" helps the user to search products and compare the price of the particular product and shows the least price of the product. Nowadays e-shopping systems use the Internet as its primary medium for transactions. E-shopping has grown in popularity over the years, mainly because people find it easy to buy number of products comfortably from their places. This technology is used to improve the customer’s needs which include faster response time. Agent for e-Shopping creates connectivity on an anytime-anywhere & any basis to provide the specific products required by the customers based on optimization and scalability. When a user search for a particular product the agent search that product on the site which has been given and compare that particular products price and it will show the least price on the right side. The conclusion shows that the system can help customers to save time for Internet shopping.

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10

Wakulicz-Deja, Alicja, and Małgorzata Przybyła-Kasperek. "Multi-Agent Decision Taking System." Fundamenta Informaticae 101, no. 1-2 (2010): 125–41. http://dx.doi.org/10.3233/fi-2010-280.

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11

Peña, Joaquin, Michael G. Hinchey, and Antonio Ruiz-Cortés. "Multi-agent system product lines." Communications of the ACM 49, no. 12 (December 2006): 82–84. http://dx.doi.org/10.1145/1183236.1183272.

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12

VALERA-ROMÁN, Adrián, Diego MATEOS-MATILLA, Eduardo OLIVA-RUBIO, and Álvaro PAULE-PEREDA. "Multi-Agent Vehicle Share System." ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL 8, no. 1 (January 18, 2019): 27. http://dx.doi.org/10.14201/adcaij2019812735.

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13

Tweedale, Jeffrey, and Lakhmi C. Jain. "Interoperability within Multi-Agent System." Journal of Intelligent & Fuzzy Systems 20, no. 1,2 (2009): 83–88. http://dx.doi.org/10.3233/ifs-2009-0417.

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14

Štula, Maja, Darko Stipaničev, and Josip Maras. "Distributed Computation Multi-agent System." New Generation Computing 31, no. 3 (July 2013): 187–209. http://dx.doi.org/10.1007/s00354-012-303-8.

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15

Wyai, Loh Chee, Cheah WaiShiang, and Marlene Valerie AiSiok Lu. "Agent Negotiation Patterns for Multi Agent Negotiation System." Advanced Science Letters 24, no. 2 (February 1, 2018): 1464–69. http://dx.doi.org/10.1166/asl.2018.10771.

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16

Botchkaryov, Alexey. "Coscheduling Spatial Self-organization and Distributed Data Collection in Multi-agent System." Advances in Cyber-Physical Systems 7, no. 2 (December 16, 2022): 76–82. http://dx.doi.org/10.23939/acps2022.02.076.

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The problem of coscheduling spatial self-organization control processes and distributed data collection processes in a multi-agent system has been considered. The goal of coscheduling is to find and use the possibilities of functional coordination of these processes and increase the efficiency of the multi-agent system due to their parallel execution. An analysis of the main features of spatial self-organization tasks that affect the solution of the problem of coscheduling has been carried out. Variants of the mobile agent robotic platform configuration and the problem of the dependence of spatial self-organization algorithms on the type of robotic platform have been considered. A method of coscheduling of spatial self-organization and distributed data collection by coordinated parallel execution of the corresponding data collection process and the process of controlling mobile agent motion has been proposed. The method of coscheduling is implemented using the interaction protocol of these processes and the algorithm for planning their parallel execution using functional decomposition. The simulation results of the proposed method of coscheduling are given. It is proved that the proposed method of coscheduling provides acceleration of computations in the decision-making module of the mobile agent due to more efficient parallelization. On average, for typical values of parameters of control processes, the proposed method of coscheduling provides acceleration of computations in the decision-making module of the mobile agent by 40.6 %.

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17

Monteiro, Thibaud, Daniel Roy, and Didier Anciaux. "Multi-site coordination using a multi-agent system." Computers in Industry 58, no. 4 (May 2007): 367–77. http://dx.doi.org/10.1016/j.compind.2006.07.005.

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18

Ma, You Jie, Fan Ting Kong, and Xue Song Zhou. "Summary on Research of Agent and Multi-Agent System." Advanced Materials Research 542-543 (June 2012): 1380–83. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1380.

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Distributed artificial intelligence is an important branch of the artificial intelligence， Agent and Multi-agent system are important aspects of distributed artificial intelligence research. This paper mainly introduce some research and exiting problems about Agent and Multi-agent system in recent years, including the Agent concept, characteristics and structure, Multi-agent system concept, structure and the coordination problem. Finally, I look forward to the development trend of Agent and Multi-agent system.

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19

Dobrynin, Alexey Sergeyevich, Alexander Sergeyevich Koynov, and Marina Vladimirovna Purgina. "Agent model for multi-agent organizational system: economic aspect." Vestnik of Astrakhan State Technical University. Series: Economics 2019, no. 4 (December 16, 2019): 14–20. http://dx.doi.org/10.24143/2073-5537-2019-4-14-20.

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Modeling the behavior of social and economic systems plays an important role in various fields of knowledge. An important task is the prediction of the behavior of such systems and their states in the future, for the adoption of proactive and corrective management decisions. Despite the constant development of game theory and other disciplines of a socio-economic (cybernetic) profile, the issue of a generalized formalized description of such systems consisting of active elements remains relevant. Significant difficulties arise with the formal description of any systems that contain active elements (people), due to the human factor and the lack of reliable knowledge about the features of the human brain. Many theories, in particular the theory of management of organizational systems, use the idea of an “economic” person as a hypothesis, whose preferences can be described by the objective cost and effect functions, which is typical for “western” scientific trends. In most cases, the developers of such theories do not propose anything concrete, but merely shift the responsibility to decision makers who are invited to build all the models on their own. It has been stated that so far many social and economic processes are considered as strategic games and zero-sum games, which leaves its mark on the decision-making process. An agent model for multi-agent organizational systems has been formed, which can be used to develop planning, incentive mechanisms that are focused on the needs and wishes of work performers. Elements of the agent model under consideration are implemented in the system for monitoring the effectiveness of the activity of the Siberian State Industrial University.

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20

Terauchi, Atsushi, Osamu Akashi, Mitsuru Maruyama, Toshiharu Sugawara, Kensuke Fukuda, Toshio Hirotsu, Satoshi Kurihara, and Keiichi Koyanagi. "Agent Organization system for Multi-agent based Network Management." Transactions of the Japanese Society for Artificial Intelligence 22 (2007): 482–92. http://dx.doi.org/10.1527/tjsai.22.482.

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21

Montano, Bonnie Rubenstein, Victoria Yoon, Kevin Drummey, and Jay Liebowitz. "Agent learning in the multi-agent contracting system [MACS]." Decision Support Systems 45, no. 1 (April 2008): 140–49. http://dx.doi.org/10.1016/j.dss.2007.12.013.

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22

Ko, Kwang-Eun, Jeong-Soo Lee, In-Hun Jang, and Kwee-Bo Sim. "Design of network for data interaction between Robot Agents in Multi Agent Robot System (MARS)." Journal of Korean Institute of Intelligent Systems 17, no. 5 (October 25, 2007): 712–17. http://dx.doi.org/10.5391/jkiis.2007.17.5.712.

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23

YAN, Wei-Sheng, Jun-Bing LI, and Yin-Tao WANG. "Consensus for Damaged Multi-agent System." Acta Automatica Sinica 38, no. 11 (2012): 1880. http://dx.doi.org/10.3724/sp.j.1004.2012.01880.

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24

Антонов, А. А., Г. В. Дук, and С. А. Чернышев. "Framework for creation multi-agent system." Vestnik of Russian New University. Series «Complex systems: models, analysis, management», no. 2 (June 21, 2022): 109–18. http://dx.doi.org/10.18137/rnu.v9187.22.02.p.109.

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Разработана платформа для создания имитационных моделей, в основе которых лежит мультиагентный подход. Рассмотрены существующие аналоги, а также выявлены их достоинства и недостатки. Фреймворк позволяет реализовать любую имитационную модель независимо от предметной области. Представлена архитектура ядра, стек технологий разработки. Для демонстрации работы создана имитационная модель предметной области «грузоперевозки». The platform has been developed for creating simulation models based on a multi-agent approach. The existing analogues were considered in the work, as well as their advantages and disadvantages were identified. The framework allows you to implement any simulation model regardless of the subject area. The article presents: core architecture, development technology stack. In conclusion, a simulation model of the subject area «Cargo transportation» was created to demonstrate the work.

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25

Memon, Zojan, Akhtar Hussain Jalbani, Mohsin Shaikh, Rafia Naz Memon, and Ahmed Ali. "Multi-Agent Communication System with Chatbots." Mehran University Research Journal of Engineering and Technology 37, no. 3 (July 1, 2018): 663–72. http://dx.doi.org/10.22581/muet1982.1803.19.

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26

Matsui, Kenji, Kenta Kimura, and Alberto Pérez. "Control Prosody using Multi-Agent System." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 2, no. 4 (March 10, 2014): 49–56. http://dx.doi.org/10.14201/adecaij20131.

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Persons who have undergone a laryngectomy have a few options to partially restore speech but no completely satisfactory device. Even though the use of an electrolarynx (EL) is the easiest way for a patient to produce speech, it does not produce a natural tone and appearance is far from normal. Because of that and the fact that none of them are hands-free, the feasibility of using a motion sensor to replace a conventional EL user interface has been explored. A mobile device motion sensor with multi-agent platform has been used to investigate on/off and pitch frequency control capability. A very small battery operated ARM-based control unit has also been developed to evaluate the motion sensor based user-interface. This control unit is placed on the wrist and the vibration device against the throat using support bandage. Two different conversion methods were used for the forearm tilt angle to pitch frequency conversion: linear mapping method and F0 template-based method A perceptual evaluation has been performed with two well-trained normal speakers and ten subjects. The results of the evaluation study showed that both methods are able to produce better speech quality in terms of the naturalness.

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27

Hasheminezhad, Mahdi, and Ardeshir Bahreininejad. "A Multi-Agent Taxi Dispatching System." International Journal of Agent Technologies and Systems 2, no. 2 (April 2010): 1–10. http://dx.doi.org/10.4018/jats.2010040101.

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The taxi assignment problem may be categorized as a vehicle routing problem. ?When placed in the field of resource allocation, it is a dynamic problem in which ?the situation changes as the work progresses. This paper presents a new agent-based approach to tackle the taxi assignment problem. New parameters are ?introduced to increase the satisfaction of the drivers. The authors propose a new algorithm to improve the parameters. Simulations were also conducted to examine the efficiency of the proposed method. The results indicate the effectiveness of the proposed taxi assignment/dispatching approach.

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28

Wang, Yan Ling. "Multi-Agent Based Logistics Coordination System." Advanced Materials Research 433-440 (January 2012): 3106–11. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3106.

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Logistics supply chain system management is the integration of key business processes from end user through original logistics suppliers that provides products, services, and information that add value for customers and other stakeholders. Logistics supply chain is a network of suppliers, factories, warehouses, distribution centers and retailers where the raw materials are acquired, manufactured to products, which then are delivered to consumers. The increase of customer expectations in low cost and high services quality has put a premium on effective logistics supply chain reengineering. Many efforts have been endeavoring to improve the supply chain performance to achieve high agility without increasing costs For improved competitiveness, supply chain logistics system in the industry has become more and more important for modern businesses, especially for the major retailing corporations. Multi-agent system which can effectively process distributed large scale data is developed for the logistics supply chain coordinate system.

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29

Mizukawa, Makoto. "Special lssue: Multi-Agent Robot System." Journal of the Robotics Society of Japan 10, no. 4 (1992): 427. http://dx.doi.org/10.7210/jrsj.10.427.

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30

Pashkin. "Multi-agent Intelligent Distance Learning System." SPIIRAS Proceedings 1, no. 3 (March 17, 2014): 126. http://dx.doi.org/10.15622/sp.3.7.

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31

PÉREZ-MORÍÑIGO, Manuel, Víctor MERCHÁN-MONTERO, and José Luis MARTÍN-PÉREZ. "Learning process: Multi-Agent Tutoring System." ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL 8, no. 1 (January 18, 2019): 5. http://dx.doi.org/10.14201/adcaij201981512.

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32

Tjahjana, R. H., and R. H. S. Utomo. "Multi agent through serret-frenet system." Journal of Physics: Conference Series 1321 (October 2019): 022071. http://dx.doi.org/10.1088/1742-6596/1321/2/022071.

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33

Sarmas, Evangelos I. "The Flisvos-2016 multi-agent system." International Journal of Agent-Oriented Software Engineering 6, no. 1 (2018): 35. http://dx.doi.org/10.1504/ijaose.2018.089596.

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Sarmas, Evangelos I. "The Flisvos-2016 multi-agent system." International Journal of Agent-Oriented Software Engineering 6, no. 1 (2018): 35. http://dx.doi.org/10.1504/ijaose.2018.10010602.

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35

Najeeb, Moath M. "Multi-Agent System for Hadith Processing." International Journal of Software Engineering and Its Applications 9, no. 9 (September 30, 2015): 153–66. http://dx.doi.org/10.14257/ijseia.2015.9.9.13.

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36

Manev, Trajche, and Sonja Filiposka. "Semantic Aware Multi-Agent System Advantages." International Journal of Informatics and Communication Technology (IJ-ICT) 3, no. 1 (April 1, 2014): 1. http://dx.doi.org/10.11591/ijict.v3i1.pp1-12.

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<span>Internet changes the way people communicate with each other and also affects the business flow. Technology changes affect how people live and communicate with each other, but they themselves also transform and become more human like. The agent oriented programming and multi-agent systems are relatively new example technologies that manifest these changes in a multifacet way. The goal of this paper is to explore the possibilities one can obtain by combining multi agent systems with the emerging semantic web technologies. This powerful combination leads towards new types of complex system development. Using a case study example, together with a comparison with the traditional system design approach, <a name="_GoBack"></a>the paper also discusess the possibilities of semantic agent platforms and their development and shows how developers can benefit from following the standards to agent development.</span>

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37

Gandon, F., A. Poggi, G. Rimassa, and P. Turci. "Multi-Agent Corporate Memory Management System." Applied Artificial Intelligence 16, no. 9-10 (October 2002): 699–720. http://dx.doi.org/10.1080/08839510290030453.

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38

Ping, Liu, Hu Yongtong, J. Bode, and Ren shouju. "Multi-agent system for cost estimation." Computers & Industrial Engineering 31, no. 3-4 (December 1996): 731–35. http://dx.doi.org/10.1016/s0360-8352(96)00247-1.

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39

Belbachir, Assia, Amal El Fallah-Seghrouchni, Arthur Casals, and Marcia Pasin. "Smart Mobility Using Multi-Agent System." Procedia Computer Science 151 (2019): 447–54. http://dx.doi.org/10.1016/j.procs.2019.04.061.

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40

Lourdes Borrajo, M., Juan M. Corchado, Emilio S. Corchado, María A. Pellicer, and Javier Bajo. "Multi-agent neural business control system." Information Sciences 180, no. 6 (March 2010): 911–27. http://dx.doi.org/10.1016/j.ins.2009.11.028.

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41

Chatterjee, Rajib Kumar, Neha Neha, and Anirban Sarkar. "Behavioral Modeling of Multi Agent System." International Journal of Agent Technologies and Systems 7, no. 1 (January 2015): 55–78. http://dx.doi.org/10.4018/ijats.2015010104.

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Modeling interactions between agents and the Multi-Agent System (MAS) behavior based on role based collaboration among the participating agents are the key factors to design of effective MAS dynamics. In this paper, a High level Multi Agent Petri Net called HMAP has been proposed which is capable of describing, analyzing and modeling dynamics of such MAS which are characterized as asynchronous, distributed, parallel and non-deterministic agent based systems. Proposed HMAP is also effective towards modeling roles, collaborations and interactions among the heterogeneous agents in MAS environment. Moreover the HMAP is useful in formal analysis of several behavioral properties of MAS like, Reachability, Home properties, Boundedness, Liveness and Fairness. The proposed mechanism has been illustrated using a suitable case study of Medical Emergency System. Moreover, to further validate the proposed concepts of HMAP, it has been simulated using Color Petri Net based tool called CPN Tool, with some restriction.

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42

Amirgholipour, Saeed K. "Multi Agent Electronic Cargo Terminal System." Indian Journal of Science and Technology 7, no. 4 (April 20, 2014): 430–38. http://dx.doi.org/10.17485/ijst/2014/v7i4.5.

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43

Itoh, Hiroko. "Berthing Control with Multi-Agent System." Journal of the Society of Naval Architects of Japan 1998, no. 184 (1998): 639–47. http://dx.doi.org/10.2534/jjasnaoe1968.1998.184_639.

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44

Tomášek, Martin. "Multi-Agent System for Business Applications." Acta Electrotechnica et Informatica 15, no. 2 (June 1, 2015): 35–38. http://dx.doi.org/10.15546/aeei-2015-0015.

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45

Wang, An Ping, Cheng Yen Wu, and Pau Lo Hsu. "The multi-agent driving assistance system." International Journal of Vehicle Autonomous Systems 5, no. 3/4 (2007): 306. http://dx.doi.org/10.1504/ijvas.2007.016406.

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46

BENOUHIBA, T., and J. NIGRO. "An evidential cooperative multi-agent system." Expert Systems with Applications 30, no. 2 (February 2006): 255–64. http://dx.doi.org/10.1016/j.eswa.2005.07.008.

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47

Sarmas, Evangelos I. "The Flisvos-2017 multi-agent system." Annals of Mathematics and Artificial Intelligence 84, no. 1-2 (June 2, 2018): 35–56. http://dx.doi.org/10.1007/s10472-018-9587-9.

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48

Drumond, Lucas, and Rosario Girardi. "A multi-agent legal recommender system." Artificial Intelligence and Law 16, no. 2 (March 29, 2008): 175–207. http://dx.doi.org/10.1007/s10506-008-9062-8.

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49

M.Ibrahim, Najhan, Mohd Fadzil Hassan, and Muhammad Amrullah DRS Nasrul. "Multi-Agent System in Web Services." International Journal on Perceptive and Cognitive Computing 10, no. 1 (January 28, 2024): 40–50. http://dx.doi.org/10.31436/ijpcc.v10i1.429.

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The term "service-oriented architecture" (SOA) refers to a software paradigm for creating systems made up of a variety of services that interact with one another to accomplish a certain task. The communications involve more than just transmitting data back and forth; they also connect two or more services to coordinate the required operations. Cross-platform communication is necessary for the coordinating process when services are spread across several platforms. Several web service standards and specifications are used in the present SOA implementation. Based on the prototype's implementation and simulation, this proposed research study has been validated and evaluated. The suggested cross-platform communications architecture is implemented using NetBeans, JADE, WSIG, and OWL-S. An integrated development environment for Java is offered by Oracle in the form of NetBeans. Telecom Italia's Java Agent DEvelopment Framework (JADE) is an agent software framework that is entirely built in the Java language. Web Service Integration Gateway (WSIG), which helps to facilitate JADE agent services being called by Web service clients. The core fundamental engine of the suggested framework is OWL-S. It is a web ontology language used to describe Semantic Web Services in the Semantic Web's OWL-based framework. A quantitative approach is used in this study's performance analysis and comparative investigation for evaluation and validation. The prototype's major element is the Java agent development framework (JADE), which was used to create a multi-agent system for the agent-based MOM framework that has been presented. The creation of the multi-agent systems was facilitated by the JADE platform. JADE 3.7 was the version that was employed. Two key features of JADE are a FIPA-compliant agent platform and a package for creating Java agents. The implementation results show that the proposed agent-based MOM framework was successful communicate between multiple types of SOA application with a better performance of the average of round-trip time where the proposed framework was successful in responding to all the requests.

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50

Zavalishchin, D. S. "Multi-agent transport system control problem." Herald of the Ural State University of Railway Transport, no. 2 (2024): 23–28. http://dx.doi.org/10.20291/2079-0392-2024-2-23-28.

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A new class of control problems for a certain transport system is considered. The peculiarity of the system is the variable number of participants in the control process. The regrouping of participants, along with their unification and dispersal, is determined by the specified target points of visit, the initial point of departure and the final point of completion of the system’s movement, and the constructed trajectories. The structure of a multi-agent transport system implies the presence of primary and secondary carriers, with the former being able to transport the latter at some stages. It is at such moments that the number of participants in the control process changes. In the constructed mathematical model of the movements of the system under consideration and its control, a hybrid system of differential equations with switching is obtained, containing continuous and discrete components. The problem of finding optimal routes under certain constraints is solved.

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