Journal articles: 'Agent-based information systems'

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Das, Subrata. "Agent-based information fusion." Information Fusion 11, no. 3 (July 2010): 216–19. http://dx.doi.org/10.1016/j.inffus.2010.01.008.

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Ehrler, Lars, Martin Fleurke, Maryam Purvis, and Bastin Tony Roy Savarimuthu. "Agent-based workflow management systems (WfMSs)." Information Systems and e-Business Management 4, no. 1 (November 8, 2005): 5–23. http://dx.doi.org/10.1007/s10257-005-0010-9.

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Abdalla, Reem, and Alok Mishra. "Using Agent-Based Methodologies in Healthcare Information Systems." Cybernetics and Information Technologies 18, no. 2 (June 1, 2018): 123–32. http://dx.doi.org/10.2478/cait-2018-0033.

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Abstract This paper carries out a comparative analysis to determine the advantages and the stages of two agent-based methodologies: Multi-agent Systems Engineering (MaSE) methodology, which is designed specifically for an agent-based and complete lifecycle approach, while also being appropriate for understanding and developing complex open systems; Agent Systems Methodology (ASEME) suggests a modular Multi-Agent System (MAS) development approach and uses the concept of intra-agent control. We also examine the strengths and weaknesses of these methodologies and the dependencies between their models and their processes. Both methodologies are applied to develop The Guardian Angle: Patient-Centered Health Information System (GA: PCHIS), which is an example of agent-based applications used to improve health care information systems.

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Zarour, Nacer eddine, and Sabrina Bouzidi. "Coalition Formation for Cooperative Information Agent-Based Systems." International Journal of Computers Communications & Control 1, no. 3 (July 1, 2006): 85. http://dx.doi.org/10.15837/ijccc.2006.3.2297.

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The communication technology evolution led to an increase of the carried out services’ and tasks’ number. The aim of actual research in the cooperation and particularly the negotiation between agents is to reach a coherent global state of the multiagent system by favoring agents’ synergy. In this paper, we propose a coalition formation-based negotiation model for the task allocation in the cooperative information agent-based systems. In this model, the agent that activates a negotiation seeks partners for achieving a complex task. The way that the partners take part in a coalition is done one by one according to the choice of all the coalition members. This choice is based on a multicriterion analysis. Some obtained experimental results show the suggested model performances.

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Tomás, V. R., I. Martí, J. J. Martínez, and A. Sáez. "Agent-based test-bed for road information systems." IET Intelligent Transport Systems 6, no. 4 (December 1, 2012): 404–12. http://dx.doi.org/10.1049/iet-its.2011.0128.

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Tang, Chao, Li Da Xu, and Shan Feng. "An agent-based geographical information system." Knowledge-Based Systems 14, no. 5-6 (August 2001): 233–42. http://dx.doi.org/10.1016/s0950-7051(01)00101-0.

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Hou, Jian, Mengfan Xiang, and Zuohua Ding. "Group Information Based Nonlinear Consensus for Multi-Agent Systems." IEEE Access 7 (2019): 26551–57. http://dx.doi.org/10.1109/access.2019.2897600.

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Rey, E. Mosqueira, A. Alonso Betanzos, B. Guijarro Berdinas, D. Alonso Rios, and J. Lago Pineiro. "A Snort-based agent for a JADE multi-agent intrusion detection system." International Journal of Intelligent Information and Database Systems 3, no. 1 (2009): 107. http://dx.doi.org/10.1504/ijiids.2009.023041.

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Allen, Peter M., and Liz Varga. "A co–Evolutionary Complex Systems Perspective on Information Systems." Journal of Information Technology 21, no. 4 (December 2006): 229–38. http://dx.doi.org/10.1057/palgrave.jit.2000075.

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The co-evolution of information systems (IS) and the processes that underpin the construction and development of IT systems are explained from a complex systems perspective. Evolution operates at the microscopic level; in organizations, this is the individual or agent. Each agent has an idiosyncratic view of the organization, using to some extent personal constructs in dealing with the reality of organizational life. These objects or constructs can be described and measured by most agents; they are well defined. Many of these objects are represented in electronic, IT systems. Each agent also has their own view as to how they know what they know, that is, their epistemology, which we argue is their IS, and is wider than the IT systems they use. The IS of each agent co-evolves, by interaction with other agents, based on the agent's view of reality. The interaction of all agents constitutes the organization. Even more importantly, different values and interests motivate each agent. This is their axiology and it is what motivates them to learn and to develop their IS. An agent-based axiological framework is essential to understanding the evolution of organizations. It is the interaction of agents that builds consensus as to the shared reality of the organization, and this affects each agent's ability and motivation to evolve IS further. In addition, we propose that it is time that IT systems included modelling capabilities, based on multi-agent representations of the organization and its context, to explore and support strategic thinking and decision making.

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Niazi, Muaz, and Amir Hussain. "Agent-based computing from multi-agent systems to agent-based models: a visual survey." Scientometrics 89, no. 2 (August 5, 2011): 479–99. http://dx.doi.org/10.1007/s11192-011-0468-9.

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Manvi, Sunilkumar S., and Pallapa Venkataram. "An Agent-Based Best Effort Routing Technique for Load Balancing." Informatica 17, no. 3 (January 1, 2006): 407–26. http://dx.doi.org/10.15388/informatica.2006.146.

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Ni, Jiarui, Dan Luo, Yuming Ou, and Chao Luo. "Agent-based evolutionary optimisation of trading strategies." International Journal of Intelligent Information and Database Systems 2, no. 1 (2008): 25. http://dx.doi.org/10.1504/ijiids.2008.017243.

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Castillo, Jose Miguel, Sascha Ossowski, and Luis Pastor. "MECIMPLAN: an agent-based methodology for planning." International Journal of Intelligent Information and Database Systems 3, no. 2 (2009): 125. http://dx.doi.org/10.1504/ijiids.2009.025159.

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Belavic, Rebeka, Marko Basuga, Vedran Podobnik, Ana Petric, and Ignac Lovrek. "Agent-based social networking for mobile user." International Journal of Intelligent Information and Database Systems 4, no. 6 (2010): 599. http://dx.doi.org/10.1504/ijiids.2010.036895.

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Sugumaran, Vijayan, Andreas J. Dietrich, and Stefan Kirn. "Supporting mass customization with agent-based coordination." Information Systems and e-Business Management 4, no. 1 (July 13, 2005): 83–106. http://dx.doi.org/10.1007/s10257-005-0006-5.

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Li, Xiaoqing, Ali R. Montazemi, and Yufei Yuan. "Agent-based buddy-finding methodology for knowledge sharing." Information & Management 43, no. 3 (April 2006): 283–96. http://dx.doi.org/10.1016/j.im.2005.07.001.

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Bentahar, Jamal, Francesca Toni, John‐Jules Ch Meyer, and Jihad Labban. "A security framework for agent‐based systems." International Journal of Web Information Systems 3, no. 4 (December 20, 2007): 341–62. http://dx.doi.org/10.1108/17440080710848125.

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Fowler, Jerry, Brad Perry, Marian Nodine, and Bruce Bargmeyer. "Agent-based semantic interoperability in infosleuth." ACM SIGMOD Record 28, no. 1 (March 1999): 60–67. http://dx.doi.org/10.1145/309844.310060.

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Chen, Bo, David D. Linz, and Harry H. Cheng. "XML-based agent communication, migration and computation in mobile agent systems." Journal of Systems and Software 81, no. 8 (August 2008): 1364–76. http://dx.doi.org/10.1016/j.jss.2007.10.026.

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20

Cardoso, Rafael C., and Angelo Ferrando. "A Review of Agent-Based Programming for Multi-Agent Systems." Computers 10, no. 2 (January 27, 2021): 16. http://dx.doi.org/10.3390/computers10020016.

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Intelligent and autonomous agents is a subarea of symbolic artificial intelligence where these agents decide, either reactively or proactively, upon a course of action by reasoning about the information that is available about the world (including the environment, the agent itself, and other agents). It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others. In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent systems. In particular, we discuss both veteran (still maintained) and novel agent programming languages, their extensions, work on comparing some of these languages, and applications found in the literature that make use of agent programming.

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Chornous, G. "AGENT-BASED MODEL OF INTELLIGENT INFORMATION CONTROL SYSTEMS IN ECONOMICS." Bulletin of Taras Shevchenko National University of Kyiv Economics, no. 178 (2016): 41–47. http://dx.doi.org/10.17721/1728-2667.2016/178-1/7.

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Bui, Tung. "Building agent-based corporate information systems: An application to telemedicine." European Journal of Operational Research 122, no. 2 (April 2000): 242–57. http://dx.doi.org/10.1016/s0377-2217(99)00231-3.

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Hacini, Salima, Zahia Guessoum, and Mohamed Cheikh. "False Alarm Reduction Using Adaptive Agent-Based Profiling." International Journal of Information Security and Privacy 7, no. 4 (October 2013): 53–74. http://dx.doi.org/10.4018/ijisp.2013100105.

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In this paper the authors propose a new efficient anomaly-based intrusion detection mechanism based on multi-agent systems. New networks are particularly vulnerable to intrusion, they are often attacked with intelligent and skilful hacking techniques. The intrusion detection techniques have to deal with two problems: intrusion detection and false alarms. The issue of false alarms has an important impact on the success of the anomaly-based intrusion detection technologies. The purpose of this paper is to improve their accuracy by detecting real attacks and by reducing the number of unnecessary generated alerts. The authors' intrusion detection mechanism relies on a set of agents to ensure the detection and the adaptation of normal profile to support the legitimate dynamic changes that occur and are the cause of high rate of false alarms.

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Andonoff, Eric, Wassim Bouaziz, Chihab Hanachi, and Lotfi Bouzguenda. "An Agent-Based Model for Autonomic Coordination of Inter-Organizational Business Processes." Informatica 20, no. 3 (January 1, 2009): 323–42. http://dx.doi.org/10.15388/informatica.2009.254.

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Agrawal, Manish, and Kaushal Chari. "Negotiation Behaviors in Agent-Based Negotiation Support Systems." International Journal of Intelligent Information Technologies 5, no. 1 (January 2009): 1–23. http://dx.doi.org/10.4018/jiit.2009010101.

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Cartwright, Julyan H. E. "AGENT-BASED SOCIAL SIMULATION: A DYNAMICAL-SYSTEMS VIEWPOINT." Cybernetics and Systems 41, no. 4 (May 28, 2010): 281–86. http://dx.doi.org/10.1080/01969721003778527.

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Kim, Kyu-Il, Joo-Chang Lee, Won-Gil Choi, Eun-Ju Lee, and Ung-Mo Kim. "A Delegation Model based on Agent in Distributed Systems." Journal of Information Processing Systems 3, no. 2 (December 31, 2007): 82–88. http://dx.doi.org/10.3745/jips.2008.3.2.082.

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Corradini, Flavio, Leonardo Mariani, and Emanuela Merelli. "An agent-based approach to tool integration." International Journal on Software Tools for Technology Transfer 6, no. 3 (August 2004): 231–44. http://dx.doi.org/10.1007/s10009-004-0158-5.

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Foued, Barouni, Daoud Ait Kadi, Sehl Mellouli, and Angel Ruiz. "A reputation-based model for semi-competitive multi-agent systems." International Journal of Intelligent Information and Database Systems 3, no. 2 (2009): 146. http://dx.doi.org/10.1504/ijiids.2009.025160.

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Pintea, Camelia-M. "A Unifying Survey of Agent-Based Approaches for Equality-Generalized Traveling Salesman Problem." Informatica 26, no. 3 (January 1, 2015): 509–22. http://dx.doi.org/10.15388/informatica.2015.61.

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31

Wasesa, Meditya, Andries Stam, and Eric van Heck. "Investigating agent-based inter-organizational systems and business network performance." Journal of Enterprise Information Management 30, no. 2 (March 6, 2017): 226–43. http://dx.doi.org/10.1108/jeim-07-2015-0069.

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Purpose From the theoretical perspectives of both multi-agent systems and smart business networks, empirical studies analyzing agent-based inter-organizational systems (ABIOS) in a real-life business setting are rare. The purpose of this paper is to investigate the impact of ABIOS on the performance of business networks. Design/methodology/approach This study presents a theoretical conceptual model portraying the influence of ABIOS on clients’ coordination structure and information architecture; and the impact of those structural alterations on business network performance in terms of the coordination, agility, and informational performances. To validate the model, a cross-case analysis was conducted in three logistics cases, namely, warehousing, freight forwarding, and intermodal transportation. Findings The application of ABIOS requires adjustments to the information architecture or the coordination structure, or both. Subsequently, those structural adjustments will stimulate improvements in the coordination, agility, and informational performances. Research limitations/implications The assessment of the clients’ performance improvement is done at the company level not at an aggregate network level. Moreover, the study only covers cases from the logistics sector. Practical implications This study explains the structural consequences of ABIOS applications. The adoption of an inter-organizational system is a strategic decision that requires support from multi-stakeholders. While the applications of ABIOS can offer performance improvement opportunities, adjustments must be made to the existing coordination structure or the information architecture, or both. Originality/value This study contributes to the smart business network literature and the ABIOS literature by presenting a validated conceptual model explaining the interplay among ABIOS, the coordination structure, informational structure, and business network performance, namely, the coordination, agility, and informational performances.

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32

Brown, Daniel G., and Yichun Xie. "Spatial agent‐based modelling." International Journal of Geographical Information Science 20, no. 9 (October 2006): 941–43. http://dx.doi.org/10.1080/13658810600830491.

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JENNINGS, N. R., P. FARATIN, M. J. JOHNSON, T. J. NORMAN, P. O'BRIEN, and M. E. WIEGAND. "AGENT-BASED BUSINESS PROCESS MANAGEMENT." International Journal of Cooperative Information Systems 05, no. 02n03 (June 1996): 105–30. http://dx.doi.org/10.1142/s0218843096000051.

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This paper describes work undertaken in the ADEPT (Advanced Decision Environment for Process Tasks) project towards developing an agent-based infrastructure for managing business processes. We describe how the key technology of negotiating, service providing, autonomous agents was realized and demonstrate how this was applied to the BT (British Telecom) business process of providing a customer quote for network services.

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Meng, Yan. "Agent-based reconfigurable architecture for real-time object tracking." Journal of Real-Time Image Processing 4, no. 4 (March 17, 2009): 339–51. http://dx.doi.org/10.1007/s11554-009-0116-2.

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Norman, Timothy J., Alun Preece, Stuart Chalmers, Nicholas R. Jennings, Michael Luck, Viet D. Dang, Thuc D. Nguyen, et al. "Agent-based formation of virtual organisations." Knowledge-Based Systems 17, no. 2-4 (May 2004): 103–11. http://dx.doi.org/10.1016/j.knosys.2004.03.005.

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Kaeri, Yuki, Kenji Sugawara, Claude Moulin, and Thierry Gidel. "Agent-based management of support systems for distributed brainstorming." Advanced Engineering Informatics 44 (April 2020): 101050. http://dx.doi.org/10.1016/j.aei.2020.101050.

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Lanzola, G., M. Stefanelli, and S. Falasconi. "Ontology and Terminology Servers in Agent-based Health-care Information Systems." Methods of Information in Medicine 36, no. 01 (January 1997): 30–43. http://dx.doi.org/10.1055/s-0038-1634688.

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Abstract:A new research paradigm is emerging based on the multi-agent system architectural framework, allowing human and software agents to interoperate and thus cooperate within common application areas. Within a multi-agent system, the different “views of the world” of knowledgeable agents are to be bridged through their commitment to common ontologies and terminologies. We developed a general methodology for the design or integration of new components into a Health-care Information System conceived as a network of software and human agents. In our view, ontological and terminological services are entrusted to dedicated agents, namely ontology and terminology servers, allowing the configuration of suitable application ontologies for distributed applications. The role is described that such servers, operatively coordinated in order to preserve semantic coherence, should play within a distributed Health-care Information System.

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Ha *, Q. P., and H. Trinh. "Observer-based control of multi-agent systems under decentralized information structure." International Journal of Systems Science 35, no. 12 (October 10, 2004): 719–28. http://dx.doi.org/10.1080/00207720412331322975.

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Bermúdez, Jesús, Alfredo Goñi, Arantza Illarramendi, and Miren I. Bagüés. "Interoperation among agent-based information systems through a communication acts ontology." Information Systems 32, no. 8 (December 2007): 1121–44. http://dx.doi.org/10.1016/j.is.2007.02.001.

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Berges, Idoia, Jesús Bermúdez, Alfredo Goñi, and Arantza Illarramendi. "Towards a satisfactory conversion of messages among agent-based information systems." Expert Systems with Applications 40, no. 7 (June 2013): 2462–75. http://dx.doi.org/10.1016/j.eswa.2012.10.055.

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Dasarathy, Belur V. "A special issue on agent-based information fusion." Information Fusion 11, no. 3 (July 2010): 215. http://dx.doi.org/10.1016/j.inffus.2010.01.007.

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Bui, Tung, and Jintae Lee. "An agent-based framework for building decision support systems." Decision Support Systems 25, no. 3 (April 1999): 225–37. http://dx.doi.org/10.1016/s0167-9236(99)00008-1.

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Kishore, Rajiv, Hong Zhang, and R. Ramesh. "Enterprise integration using the agent paradigm: foundations of multi-agent-based integrative business information systems." Decision Support Systems 42, no. 1 (October 2006): 48–78. http://dx.doi.org/10.1016/j.dss.2004.09.011.

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Melo, Victor S., Alison R. Panisson, and Rafael H. Bordini. "Meta-Information and Argumentation in Multi-Agent Systems." iSys - Brazilian Journal of Information Systems 10, no. 3 (September 30, 2017): 74–97. http://dx.doi.org/10.5753/isys.2017.347.

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In this work we compile our research regarding meta-information in multi-agent systems. In particular, we describe some agents profiles represent- ing different attitudes which describe how agents consider meta-information in their decisions-making and reasoning processes. Furthermore, we describe how we have combined different meta-information available in multi-agent systems with an argumentation-based reasoning mechanism. In our approach, agents are able to decide more conflicts between information/arguments, given that they are able to use different meta-information (often combined) to decide between such conflicting information. Our framework for meta-information in multi- agent systems was implemented based on a modular architecture, thus other meta-information can be added, as well as different meta-information can be combined in order to create new agents profiles. Therefore, in our approach, different agents profiles can be instantiated for different application domains, allowing flexibility in the choice of how agents will deal with conflicting infor- mation in those particular domains.

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Ryoke, Mina, and Yoshiteru Nakamori. "Agent-based approach to complex systems modeling." European Journal of Operational Research 166, no. 3 (November 2005): 717–25. http://dx.doi.org/10.1016/j.ejor.2004.03.041.

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SUKONSCHIKOV, ALEXEY A., ANATOLY N. SHVETSOV, IGOR A. ANDRIANOV, and DMITRIY V. KOCHKIN. "PRINCIPLES OF BUILDING SELF-ORGANIZING INFORMATION AND TELECOMMUNICATION SYSTEMS." Cherepovets State University Bulletin 1, no. 100 (2021): 56–67. http://dx.doi.org/10.23859/1994-0637-2021-1-100-4.

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The article discusses the basic foundations of the functioning and evolution of complex distributed information and telecommunication systems (ITS) in the neuro-fuzzy agent-based paradigm. The formalization principles for such systemsareproposed:goal structuring, agent orientation, hierarchical intellectual organization, modularity of intelligent agents, structural and functional flexibility of intelligent agents, single mathematical apparatus, self-development and system evolution.The concept of a distributed intelligent ITS as a geographically distributed multi-level hierarchical set of hardware and software controlled by agent-based systems is introduced.

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Ma, Yinglong, Shipeng Zhang, Yuancheng Li, Zheng Yi, and Shaohua Liu. "An approach for multi-agent coordination based on semantic approximation." International Journal of Intelligent Information and Database Systems 3, no. 2 (2009): 163. http://dx.doi.org/10.1504/ijiids.2009.025161.

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Paranjape, Raman, Simerjit Gill, Sara Ghoreishi Nejad, and Robert Martens. "An agent-based simulation system for modelling a diabetic patient." International Journal of Intelligent Information and Database Systems 4, no. 3 (2010): 264. http://dx.doi.org/10.1504/ijiids.2010.034083.

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Liu, James N. K., and M. K. Ho. "An intelligent agent-based system for multilingual financial news digest." International Journal of Intelligent Information and Database Systems 4, no. 4 (2010): 337. http://dx.doi.org/10.1504/ijiids.2010.035580.

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Mathieu, Philippe. "Editorial for the Special Issue on ‘Agent-Based Artificial Markets’." Information 9, no. 9 (September 3, 2018): 225. http://dx.doi.org/10.3390/info9090225.

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Journal articles on the topic 'Agent-based information systems'

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