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Статті в журналах з теми "Multi-agent system analysis":
Simankov, V. S., and Yu V. Dubenko. "SYSTEM ANALYSIS IN HIERARCHICAL INTELLIGENT MULTI-AGENT SYSTEMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 201 (March 2021): 33–46. http://dx.doi.org/10.14489/vkit.2021.03.pp.033-046.
Yu, Miao, and Zhi Cai. "The Dynamics Analysis of the Robot Polishing System by the Multi-Agent System." Key Engineering Materials 419-420 (October 2009): 601–4. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.601.
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.
Pavlenko, Viacheslav, Volodymyr Manuylov та Volodymyr Kuzhel. "Сase-systems for development of multiagent system (MAS) in the system of diagnostics and maintenance of vehicles". Journal of Mechanical Engineering and Transport 13, № 1 (2021): 87–93. http://dx.doi.org/10.31649/2413-4503-2021-13-1-87-93.
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.
Chatterjee, Rajib Kumar, Mangilal Sharma, and Anirban Sarkar. "Modeling of Multi Agent System: From Analysis to Design." International Journal of Software Engineering and Its Applications 10, no. 12 (December 31, 2016): 149–68. http://dx.doi.org/10.14257/ijseia.2016.10.12.13.
Ma, Lizhu, and Xin Zhang. "Hierarchical Social Network Analysis Using a Multi-Agent System." International Journal of Agent Technologies and Systems 5, no. 3 (July 2013): 14–32. http://dx.doi.org/10.4018/ijats.2013070102.
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.
Lavendelis, Egons, and Janis Grundspenkis. "Requirements analysis of Multi-Agent Based Intelligent Tutoring Systems." Scientific Journal of Riga Technical University. Computer Sciences 38, no. 38 (January 1, 2009): 37–47. http://dx.doi.org/10.2478/v10143-009-0003-0.
Yi-Jen Su, Yi-Jen Su, and Sheng-Yuan Yang Yi-Jen Su. "A User-friendly Cloud-based Multi-agent Information System for Smart Energy-saving." 網際網路技術學刊 25, no. 2 (March 2024): 293–300. http://dx.doi.org/10.53106/160792642024032502011.
Дисертації з теми "Multi-agent system analysis":
Hossack, John A. "A multi-agent system for automated post-fault disturbance analysis." Thesis, University of Strathclyde, 2005. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21606.
Kontarinis, Dionysios. "Debate in a multi-agent system : multiparty argumentation protocols." Thesis, Paris 5, 2014. http://www.theses.fr/2014PA05S025/document.
In this thesis multi-agent argumentation debates are studied. Our work is motivated by the issues which are raised when a large number of users interact and debate on the Web, by exchanging arguments on various topics. These issues are raised on the levels of representing the debating users' knowledge, representing the debate, computing the debate's conclusions, evaluating the debate's quality, defining specific protocols for user interaction, and studying debate strategies which users employ in order to achieve particular goals. This thesis' contribution consists in: a) proposing a way to model a multi-agent argumentation debate where the participants have different types of expertise, and proposing a way to aggregate their opinions; b) offering support to the agent who is arbitrating a debate, proposing a way to evaluate the quality of a debate on the basis of how confident we can be on its conclusions, and proposing solutions for improving the quality of a debate which lacks definite conclusions; c) offering support to the debating agents in order to determine which arguments they should put forward, studying dynamic argumentation systems, studying the potential ways in which an agent can influence a dynamic argumentation system in order to achieve his goal, studying the minimal change allowing an agent to achieve his goal, studying several argumentation strategies based on minimal change; d) defining, studying and evaluating multi-agent argumentation protocols, defining protocols of different types (1) based on numerical argument evaluation and (2) based on argument extensions, using different techniques to ensure a debate's coherence while ensuring some liberty of expression to the agents, and finally performing an important number of experiments (on debates) in order to test various strategies and evaluate them with respect to specific criteria
Kontarinis, Dionysios. "Debate in a multi-agent system : multiparty argumentation protocols." Electronic Thesis or Diss., Paris 5, 2014. http://www.theses.fr/2014PA05S025.
In this thesis multi-agent argumentation debates are studied. Our work is motivated by the issues which are raised when a large number of users interact and debate on the Web, by exchanging arguments on various topics. These issues are raised on the levels of representing the debating users' knowledge, representing the debate, computing the debate's conclusions, evaluating the debate's quality, defining specific protocols for user interaction, and studying debate strategies which users employ in order to achieve particular goals. This thesis' contribution consists in: a) proposing a way to model a multi-agent argumentation debate where the participants have different types of expertise, and proposing a way to aggregate their opinions; b) offering support to the agent who is arbitrating a debate, proposing a way to evaluate the quality of a debate on the basis of how confident we can be on its conclusions, and proposing solutions for improving the quality of a debate which lacks definite conclusions; c) offering support to the debating agents in order to determine which arguments they should put forward, studying dynamic argumentation systems, studying the potential ways in which an agent can influence a dynamic argumentation system in order to achieve his goal, studying the minimal change allowing an agent to achieve his goal, studying several argumentation strategies based on minimal change; d) defining, studying and evaluating multi-agent argumentation protocols, defining protocols of different types (1) based on numerical argument evaluation and (2) based on argument extensions, using different techniques to ensure a debate's coherence while ensuring some liberty of expression to the agents, and finally performing an important number of experiments (on debates) in order to test various strategies and evaluate them with respect to specific criteria
Alam, S. M. Shafiul. "Multi-agent estimation and control of cyber-physical systems." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/20494.
Electrical and Computer Engineering
Balasubramaniam Natarajan
A cyber-physical system (CPS) typically consists of networked computational elements that control physical processes. As an integral part of CPS, the widespread deployment of communicable sensors makes the task of monitoring and control quite challenging especially from the viewpoint of scalability and complexity. This research investigates two unique aspects of overcoming such barriers, making a CPS more robust against data explosion and network vulnerabilities. First, the correlated characteristics of high-resolution sensor data are exploited to significantly reduce the fused data volume. Specifically, spatial, temporal and spatiotemporal compressed sensing approaches are applied to sample the measurements in compressed form. Such aggregation can directly be used in centralized static state estimation even for a nonlinear system. This approach results in a remarkable reduction in communication overhead as well as memory/storage requirement. Secondly, an agent based architecture is proposed, where the communicable sensors (identified as agents) also perform local information processing. Based on the local and underdetermined observation space, each agent can monitor only a specific subset of global CPS states, necessitating neighborhood information exchange. In this framework, we propose an agent based static state estimation encompassing local consensus and least square solution. Necessary bounds for the consensus weights are obtained through the maximum eigenvalue based convergence analysis and are verified for a radial power distribution network. The agent based formulation is also applied for a linear dynamical system and the consensus approach is found to exhibit better and more robust performance compared to a diffusion filter. The agent based Kalman consensus filter (AKCF) is further investigated, when the agents can choose between measurements and/or consensus, allowing the economic allocation of sensing and communication tasks as well as the temporary omission of faulty agents. The filter stability is guaranteed by deriving necessary consensus bounds through Lyapunov stability analysis. The states dynamically estimated from AKCF can be used for state-feedback control in a model predictive fashion. The effect of lossy communication is investigated and critical bounds on the link failure rate and the degree of consensus that ensure stability of the agent based control are derived and verified via simulations.
Yang, Ang Information Technology & Electrical Engineering Australian Defence Force Academy UNSW. "A networked multi-agent combat model : emergence explained." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2007. http://handle.unsw.edu.au/1959.4/38823.
Dal, col Laura. "On distributed control analysis and design for Multi-Agent systems subject to limited information." Thesis, Toulouse, INSA, 2016. http://www.theses.fr/2016ISAT0034/document.
Multi-agent systems are dynamical systems composed of multiple interacting elements known as agents . Each agent is a dynamical system with two characteristics. First, it is capable of autonomous action—that is, it is able to evolve according to a self-organised behavior, which is not influenced by the external environment. Second, it is able to exchange information with other agents in order to accomplish complex tasks, such as coordination, cooperation, and conflict resolution. One commonly studied problem in multi-agent systems is synchronization. The agents are synchronized when their time evolutions converge to a common trajectory. Many real-world applications, such as flocking and formation control, can be cast as synchronization problems. Agent synchronization can be achieved using different approaches. In this thesis, we propose distributed and centralized control paradigms for the synchronization of multi-agent systems. We develop necessary and sufficient conditions for the synchronization of multi-agent systems, composed by identical linear time-invariant agents, us- ing a Lyapunov-based approach. Then we use these conditions to design distributed synchronization controllers. Then, we extend this result to multi-agent systems subject to external disturbances enforcing disturbance rejection with 퐻 ∞ control techniques. Furthermore, we extend the analysis to multi-agent systems with actuator constraints using LMI-based anti-windup techniques. We test the proposed control design strategies in simulated examples among which two are inspired by real-world applications. In the first, we study airplane formation control as a synchronization problem. In the second, we analyze the delivery of video streams as a synchronization problem and we compare the results to existing controllers
Svahnberg, Mikael. "Background Analysis and Design of ABOS, an Agent-Based Operating System." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2792.
HAN, BEI. "Modeling and Analysis of Multilayer Complex Distribution System: A Multi-Agent Simulation for Decision Making." Doctoral thesis, Politecnico di Torino, 2013. http://hdl.handle.net/11583/2507530.
Saw, Tee Huu. "Evaluation of a multi-agent system for simulation and analysis of distributed denial-of-service attacks." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Dec%5FSaw.pdf.
Thesis advisor(s): James B. Michael, Mikhail Auguston. Includes bibliographical references (p. 52-54). Also available online.
Franco, Nicola. "Distributed Observer Analysis and Design." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19642/.
Книги з теми "Multi-agent system analysis":
Netherlands) EUMAS 2011 (2011 Maastricht. Multi-agent systems: 9th European workshop, EUMAS 2011, Maastricht, the Netherlands, November 14-15, 2011 : revised selected papers. Berlin: Springer, 2012.
Villatoro, Daniel. Multi-Agent-Based Simulation XII: International Workshop, MABS 2011, Taipei, Taiwan, May 2-6, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Chen, Guanrong, Wenwu Yu, Guanghui Wen, and Jinde Cao. Distributed Cooperative Control of Multi-Agent Systems. Wiley & Sons, Limited, John, 2016.
Chen, Guanrong, Wenwu Yu, Guanghui Wen, and Jinde Cao. Distributed Cooperative Control of Multi-Agent Systems. Wiley & Sons, Incorporated, John, 2016.
Chen, Guanrong, Wenwu Yu, Guanghui Wen, and Jinde Cao. Distributed Cooperative Control of Multi-Agent Systems. Wiley & Sons, Incorporated, John, 2016.
Chen, Guanrong, Wenwu Yu, Guanghui Wen, and Jinde Cao. Distributed Cooperative Control of Multi-Agent Systems. Wiley & Sons, Limited, John, 2016.
Plinere, Darja. Development of a Multi-agent System for Supply Chain Management Efficiency Improvement. RTU Press, 2021. http://dx.doi.org/10.7250/9789934226915.
Evaluation of a Multi-Agent System for Simulation and Analysis of Distributed Denial-of-Service Attacks. Storming Media, 2003.
Scown, Philip James Andrew. Knowldege needs analysis for simultaneously multi-agent real-time systems. 1997.
Liu, Cheng-Lin, and Fei Liu. Consensus Problem of Delayed Linear Multi-Agent Systems: Analysis and Design. Springer Singapore Pte. Limited, 2016.
Частини книг з теми "Multi-agent system analysis":
Jonker, Catholijn M., and Jan Treur. "Formal Analysis of Models for the Dynamics of Trust Based on Experiences." In Multi-Agent System Engineering, 221–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48437-x_18.
Rouchier, J., and F. Bousquet. "Non-merchant Economy and Multi-agent System: An Analysis of Structuring Exchanges." In Multi-Agent Systems and Agent-Based Simulation, 111–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/10692956_8.
Zanni-Merk, Cecilia, Santiago Almiron, and Dominique Renaud. "A Multi-agents System for Analysis and Diagnosis of SMEs." In Agent and Multi-Agent Systems: Technologies and Applications, 103–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22000-5_12.
Reboiro-Jato, Miguel, Daniel Glez-Peña, Hugo M. Santos, Mário S. Diniz, Carlos Lodeiro, José L. Capelo, and Florentino Fdez-Riverola. "Multi-agent System for Mass Spectrometry Analysis." In Advances in Intelligent and Soft Computing, 87–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12433-4_11.
Tanaka, Yoshikazu, and Kazuhiko Tsuda. "Model-Driven Development of Water Hammer Analysis Software for Irrigation Pipeline System." In Agent and Multi-Agent Systems: Technology and Applications, 301–17. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39883-9_25.
Kim, Taekyu, Young-Shin Han, Tae-young Kim, and Jong-Sik Lee. "Ontology Methodology Based Context Awareness Using System Entity Structure for Network Analysis." In Agent and Multi-Agent Systems: Technologies and Applications, 232–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78582-8_24.
Cabac, Lawrence, Nicolas Knaak, Daniel Moldt, and Heiko Rölke. "Analysis of Multi-Agent Interactions with Process Mining Techniques." In Multiagent System Technologies, 12–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11872283_2.
Zabłocki, Michał. "Multi-agent Processes Analysis System in Prediction Task." In Advances in Intelligent Systems and Computing, 73–84. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15147-2_7.
Goshima, Keiichi, and Hiroshi Takahashi. "Text Analysis System for Measuring the Influence of News Articles on Intraday Price Changes in Financial Markets." In Agent and Multi-Agent Systems: Technology and Applications, 341–48. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39883-9_28.
Fujiwara, Shohei, Yusuke Matsumoto, Aiko Suge, and Hiroshi Takahashi. "Constructing a Valuation System Through Patent Document Analysis." In Agents and Multi-Agent Systems: Technologies and Applications 2020, 321–30. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5764-4_30.
Тези доповідей конференцій з теми "Multi-agent system analysis":
Wang, Zhao-hui, and Sheng-rong Gong. "MAIRS: a content-based multi-agent image retrieval system." In MIPPR 2005 Image Analysis Techniques, edited by Deren Li and Hongchao Ma. SPIE, 2005. http://dx.doi.org/10.1117/12.655288.
Liu, Bo, Xinmao Zhu, and Jie Zhang. "Consensus Analysis of the Multi-agent System." In 2010 International Workshop on Chaos-Fractals Theories and Applications (IWCFTA). IEEE, 2010. http://dx.doi.org/10.1109/iwcfta.2010.102.
Su-Fang Chen. "Automation Power Dispatching sheet System based Multi-Agent." In 2009 International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA 2009). IEEE, 2009. http://dx.doi.org/10.1109/icacia.2009.5361097.
Dawson-Diaz, Nathal, and Vianca Vega-Zepeda. "Lifecycle coverage analysis via multi-agent system methodology." In 2017 6th International Conference on Software Process Improvement (CIMPS). IEEE, 2017. http://dx.doi.org/10.1109/cimps.2017.8169956.
Badih, Haissam, and Yasamin Alagrash. "Static Analysis Framework Based on Multi - Agent System." In 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). IEEE, 2020. http://dx.doi.org/10.1109/iemtronics51293.2020.9216382.
Reed, J. W. "A multi-agent system for distributed cluster analysis." In "Third International Workshop on Software Engineering for Large-Scale Multi-Agent Systems (SELMAS'04)" W16L Workshop - 26th International Conference on Software Engineering. IEE, 2004. http://dx.doi.org/10.1049/ic:20040372.
Lee, Hae-In, Hyo-Sang Shin, and Antonios Tsourdos. "Stability Analysis on the Networked Multi-Agent System." In 2018 17th European Control Conference (ECC). IEEE, 2018. http://dx.doi.org/10.23919/ecc.2018.8550052.
Korczak, Jerzy, Marcin Hernes, and Maciej Bac. "Fundamental analysis in the multi-agent trading system." In 2016 Federated Conference on Computer Science and Information Systems. IEEE, 2016. http://dx.doi.org/10.15439/2016f238.
Mohammed, Khudhair Abbas, Salama A. Mostafa, Mohd Sharifuddin Ahmad, and Moamin A. Mahmoud. "A qualitative analysis of human-agent functions for collaborative multi-agent system." In 2014 International Conference on Information Technology and Multimedia (ICIMU). IEEE, 2014. http://dx.doi.org/10.1109/icimu.2014.7066638.
Casella, G., V. Deufemia, and V. Mascardi. "A Multi-Agent System for Hand-drawn Diagram Recognition." In Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2. IEEE, 2007. http://dx.doi.org/10.1109/icdar.2007.4377013.
Звіти організацій з теми "Multi-agent system analysis":
Barber, K. S. Multi-Scale Behavioral Modeling and Analysis Promoting a Fundamental Understanding of Agent-Based System Design and Operation. Fort Belvoir, VA: Defense Technical Information Center, March 2007. http://dx.doi.org/10.21236/ada465613.
van der Mensbrugghe, Dominique. The Standard GTAP Model in GAMS, Version 7.1. GTAP Working Paper, April 2023. http://dx.doi.org/10.21642/gtap.wp92.