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Relevant bibliographies by topics / Distributed artificial intelligence

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Academic literature on the topic 'Distributed artificial intelligence'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Distributed artificial intelligence"

1

Pimple, Omkar, Umesh Saravane, and Neha Gavankar. "Cognitive Learning Using Distributed Artificial Intelligence." International Journal of Machine Learning and Computing 5, no. 1 (2015): 7–11. http://dx.doi.org/10.7763/ijmlc.2015.v5.474.

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Chaib-draa, B., R. Mandiau, and P. Millot. "Distributed artificial intelligence." ACM SIGART Bulletin 3, no. 3 (1992): 20–37. http://dx.doi.org/10.1145/140936.140937.

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Jagannathan, V., and Rajendra Dodhiawala. "Distributed artificial intelligence." ACM SIGART Bulletin, no. 95 (January 1986): 44–56. http://dx.doi.org/10.1145/1056563.1056571.

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Eduardo, Luis, and Castillo Hern. "On distributed artificial intelligence." Knowledge Engineering Review 3, no. 1 (1988): 21–57. http://dx.doi.org/10.1017/s0269888900004367.

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AbstractDistributed Artificial Intelligence has been loosely defined in terms of computation by distributed, intelligent agents. Although a variety of projects employing widely ranging methodologies have been reported, work in the field has matured enough to reveal some consensus about its main characteristics and principles. A number of prominent projects are described in detail, and two general frameworks, theSystem conceptual modeland theagent conceptual model, are used to compare the different approaches. The paper concludes by reviewing approaches to formalizing some of the more critical

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Klügl, Franziska. "Beyond Distributed Artificial Intelligence." KI - Künstliche Intelligenz 28, no. 3 (2014): 139–41. http://dx.doi.org/10.1007/s13218-014-0319-y.

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Dzitac, Ioan, and Boldur E. Bărbat. "Artificial Intelligence + Distributed Systems = Agents." International Journal of Computers Communications & Control 4, no. 1 (2009): 17. http://dx.doi.org/10.15837/ijccc.2009.1.2410.

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The connection with Wirth’s book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic

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Morse, David V. "Readings in distributed artificial intelligence." Artificial Intelligence in Engineering 6, no. 2 (1991): 103. http://dx.doi.org/10.1016/0954-1810(91)90005-9.

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Chaib-Draa, B., B. Moulin, R. Mandiau, and P. Millot. "Trends in distributed artificial intelligence." Artificial Intelligence Review 6, no. 1 (1992): 35–66. http://dx.doi.org/10.1007/bf00155579.

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9

Waters, Samuel T. "Readings in distributed artificial intelligence." Information Processing & Management 25, no. 5 (1989): 586. http://dx.doi.org/10.1016/0306-4573(89)90030-7.

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Eliëns, A. "Distributed Logic Programming for Artificial Intelligence." AI Communications 4, no. 1 (1991): 11–21. http://dx.doi.org/10.3233/aic-1991-4103.

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Dissertations / Theses on the topic "Distributed artificial intelligence"

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Sian, Satwinder Singh. "Learning in distributed artificial intelligence systems." Thesis, Imperial College London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282757.

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Rampal, Gaurav S. "Developing mobile distributed intelligent network services using RM-ODP." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ32556.pdf.

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Wei, Jin. "Modeling and Coordination of interconnected microgrids using distributed artificial intelligence approaches." Thesis, Bourgogne Franche-Comté, 2019. http://www.theses.fr/2019UBFCA021.

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À mesure que les sources renouvelables pénètrent dans le système électrique actuel pour atténuer le réchauffement planétaire et la pénurie d’énergie, le concept de microréseau (MG) permet de réduire l’impact de la production intermittente sur le réseau de services publics. Il permet d'améliorer l’automatisation et l’intelligence du réseau électrique avec des caractéristiques plug-and-play. L’intégration d’un plus grand nombre de MG dans un réseau de distribution favorise le développement du réseau intelligent. Leur coordination pourrait conduire à une grande fiabilité du système avec un faible

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Lucouw, Alexander. "Distributed fault detection and diagnostics using artificial intelligence techniques / A. Lucouw." Thesis, North-West University, 2009. http://hdl.handle.net/10394/4110.

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With the advancement of automated control systems in the past few years, the focus has also been moved to safer, more reliable systems with less harmful effects on the environment. With increased job mobility, less experienced operators could cause more damage by incorrect identification and handling of plant faults, often causing faults to progress to failures. The development of an automated fault detection and diagnostic system can reduce the number of failures by assisting the operator in making correct decisions. By providing information such as fault type, fault severity, fault location

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5

Li, Xiao-Dong Carleton University Dissertation Engineering Electrical. "DISC: a framework for coordination in a distributed artificial intelligence system." Ottawa, 1992.

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6

Balamuru, Vinay Gopal. "The Role of Intelligent Mobile Agents in Network Management and Routing." Thesis, University of North Texas, 2000. https://digital.library.unt.edu/ark:/67531/metadc2736/.

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In this research, the application of intelligent mobile agents to the management of distributed network environments is investigated. Intelligent mobile agents are programs which can move about network systems in a deterministic manner in carrying their execution state. These agents can be considered an application of distributed artificial intelligence where the (usually small) agent code is moved to the data and executed locally. The mobile agent paradigm offers potential advantages over many conventional mechanisms which move (often large) data to the code, thereby wasting available network

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Wong, Wing-ki Vicky. "An immunity-based distributed multiagent control framework." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37314348.

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Ling, Nai Man. "The application of artificial intelligence and distributed control to a robotic workcell /." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=55617.

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Wallace, Andrew Alexander. "Application of distributed artificial intelligence to the flow control of mobile robots." Thesis, Open University, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.395248.

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Khoui, Hooman. "Investigations into distributed artificial intelligence techniques for design with applications to instruments." Thesis, City University London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283157.

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Books on the topic "Distributed artificial intelligence"

1

Chen, Jie, Jérôme Lang, Christopher Amato, and Dengji Zhao, eds. Distributed Artificial Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94662-3.

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Yadav, Satya Prakash, Dharmendra Prasad Mahato, and Nguyen Thi Dieu Linh. Distributed Artificial Intelligence. Edited by Satya Prakash Yadav, Dharmendra Prasad Mahato, and Nguyen Thi Dieu Linh. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467.

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Taylor, Matthew E., Yang Yu, Edith Elkind, and Yang Gao, eds. Distributed Artificial Intelligence. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64096-5.

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N, Huhns Michael, ed. Distributed artificial intelligence. Pitman, 1987.

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5

Yokoo, Makoto, Hong Qiao, Yevgeniy Vorobeychik, and Jianye Hao, eds. Distributed Artificial Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25549-6.

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de Leon F. de Carvalho, Andre Ponce, Sara Rodríguez-González, Juan F. De Paz Santana, and Juan M. Corchado Rodríguez, eds. Distributed Computing and Artificial Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14883-5.

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Omatu, Sigeru, José Neves, Juan M. Corchado Rodriguez, Juan F. Paz Santana, and Sara Rodríguez Gonzalez, eds. Distributed Computing and Artificial Intelligence. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00551-5.

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Omatu, Sigeru, Juan F. De Paz Santana, Sara Rodríguez González, Jose M. Molina, Ana M. Bernardos, and Juan M. Corchado Rodríguez, eds. Distributed Computing and Artificial Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28765-7.

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H, Bond Alan, and Gasser Leslie George 1949-, eds. Readings in distributed artificial intelligence. M. Kaufmann, 1988.

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P, O'Hare G. M., and Jennings Nick, eds. Foundations of distributed artificial intelligence. Wiley, 1996.

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Book chapters on the topic "Distributed artificial intelligence"

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Mishra, Annu. "Distributed Artificial Intelligence." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-1.

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Yadav, Satya Prakash. "Distributed Consensus." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-5.

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Singh, Pushpa, Rajnesh Singh, Narendra Singh, and Murari Kumar Singh. "A Distributed Artificial Intelligence." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-16.

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Agarwal, Rashi, Supriya Khaitan, and Shashank Sahu. "Intelligent Agents." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-2.

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Seem, Ankur, Arpit Kumar Chauhan, Rijwan Khan, and Satya Prakash Yadav. "Distributed Artificial Intelligence for Document Retrieval." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-4.

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Gupta, Nidhi, Shailesh Singh, and Sonia Gupta. "Agora Architecture." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-10.

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Sankhyadhar, Shubhangi, and Mohit Pandey. "Test Beds for Distributed AI Research." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-11.

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Yadav, Vijay, Raghuraj Singh, and Vibhash Yadav. "Real-Time Framework Competitive Distributed Dilemma." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-12.

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Hussain, Naziya, and Preeti Rani. "Comparative Studied Based on Attack Resilient and Efficient Protocol with Intrusion Detection System Based on Deep Neural Network for Vehicular System Security." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-13.

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Rawat, Dhruv, Amit Kumar, and Suresh Kumar. "A Secure Electronic Voting System Using Decentralized Computing." In Distributed Artificial Intelligence. CRC Press, 2020. http://dx.doi.org/10.1201/9781003038467-14.

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Conference papers on the topic "Distributed artificial intelligence"

1

Jamwal, Rajender, Aman Sharma, and Tanu Sharma. "Harnessing Artificial Intelligence to Promote Spiritual Intelligence Via Social Media." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984275.

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Cuna, Federica, Maria Bossa, Fabio Gargano, Nicola Mario Mazziotta, and Pietro Betti. "Artificial Intelligence techniques for space experiments." In 2025 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP). IEEE, 2025. https://doi.org/10.1109/pdp66500.2025.00064.

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Jiang, Yuankun, Wei Zhang, Zenghai Wang, et al. "Distributed Artificial Intelligence Algorithm Design in Edge Computing Environment." In 2024 International Conference on Computing, Robotics and System Sciences (ICRSS). IEEE, 2024. https://doi.org/10.1109/icrss65752.2024.00060.

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Liang, Zhuo. "Automated Artificial Intelligence Technology in Wireless Network Systems." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939185.

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Hariharan, Shanmugasundaram, Pogula Srivani, Sreenivasulu Gogula, N. Venkateswaran, Vinay Kukreja, and Jose P. "Sustainable Smart Agriculture Advisor through Artificial Intelligence Approach." In 2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC). IEEE, 2024. https://doi.org/10.1109/icdscnc62492.2024.10939809.

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Wang, Guanyao, Zihan Zhao, Xu Wang, Yuanqi Dou, and Yuanfeng Dou. "Research on distributed energy management system based on artificial intelligence." In 2024 6th International Conference on Energy, Power and Grid (ICEPG). IEEE, 2024. https://doi.org/10.1109/icepg63230.2024.10775972.

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Wang, Guanyao, Zihan Zhao, Xu Wang, Yuanqi Dou, Yuanfeng Dou, and Zheng Liu. "Application Research of Artificial Intelligence in Distributed Energy Management System." In 2024 6th International Conference on Energy Systems and Electrical Power (ICESEP). IEEE, 2024. http://dx.doi.org/10.1109/icesep62218.2024.10652106.

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Singh, Karanbir, Deepak Muppiri, and Inderveer Chana. "Efficient Resource Management of Kubernetes Pods using Artificial Intelligence." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984409.

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Harmon, Laurel A., and Robert F. Franklin. "Distributed Artificial Intelligence: A Critical Review." In 1988 Robotics Conferences, edited by David P. Casasent, Ernest L. Hall, and Kenneth J. Stout. SPIE, 1989. http://dx.doi.org/10.1117/12.949134.

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Mohammed, Shady A., Shervin Shirmohammadi, and Sa'di Altamimi. "Artificial Intelligence-Based Distributed Network Latency Measurement." In 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2019. http://dx.doi.org/10.1109/i2mtc.2019.8826859.

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Reports on the topic "Distributed artificial intelligence"

1

Meyer, Robert A., and Susan E. Conry. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 3. Distributed Artificial Intelligence for Communication Network Management. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada197957.

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Varastehpour, Soheil, Hamid Sharifzadeh, and Iman Ardekani. A Comprehensive Review of Deep Learning Algorithms. Unitec ePress, 2021. http://dx.doi.org/10.34074/ocds.092.

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Deep learning algorithms are a subset of machine learning algorithms that aim to explore several levels of the distributed representations from the input data. Recently, many deep learning algorithms have been proposed to solve traditional artificial intelligence problems. In this review paper, some of the up-to-date algorithms of this topic in the field of computer vision and image processing are reviewed. Following this, a brief overview of several different deep learning methods and their recent developments are discussed.

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