Autonomous Intelligent Systems: Multi-Agents and Data Mining PDF Download
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Author: Vladimir Gorodetsky
Publisher: Springer
ISBN: 3540728392
Category : Computers
Languages : en
Pages : 326
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Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007, held in St. Petersburg, Russia in June 2007. The 17 revised full papers and six revised short papers presented together with four invited lectures cover agent and data mining, agent competition and data mining, as well as text mining, semantic Web, and agents.
Author: Vladimir Gorodetsky
Publisher: Springer
ISBN: 3540728392
Category : Computers
Languages : en
Pages : 326
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Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2007, held in St. Petersburg, Russia in June 2007. The 17 revised full papers and six revised short papers presented together with four invited lectures cover agent and data mining, agent competition and data mining, as well as text mining, semantic Web, and agents.
Author: Vladimir Gorodetsky
Publisher: Springer Science & Business Media
ISBN: 3540261648
Category : Computers
Languages : en
Pages : 313
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Book Description
This book constitutes the refereed proceedings of the International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2005, held in St. Petersburg, Russia in June 2005. The 17 revised full papers presented together with 5 invited papers and the abstract of an invited talk were carefully reviewed and selected from 29 submissions. The papers are organized in topical sections on agent-based data mining issues, ontologies and Web mining, and applications and case studies.
Author: Vladimir Gorodetsky
Publisher: Springer
ISBN: 9783540811558
Category : Computers
Languages : en
Pages : 303
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Book Description
Author: Andreas L. Symeonidis
Publisher: Springer Science & Business Media
ISBN: 0387257578
Category : Computers
Languages : en
Pages : 216
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Book Description
This book addresses the use of data mining for smarter, more efficient agents, as well as the challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. Following a brief review of data mining and agent technology fields, the book presents a methodology for developing multi-agent systems, describes available open-source tools, and demonstrates the application of the methodology on three different cases.
Author: Dilip Kumar Pratihar
Publisher: Springer Science & Business Media
ISBN: 3642116752
Category : Computers
Languages : en
Pages : 269
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Book Description
This research book contains a sample of most recent research in the area of intelligent autonomous systems. The contributions include: General aspects of intelligent autonomous systems Design of intelligent autonomous robots Biped robots Robot for stair-case navigation Ensemble learning for multi-source information fusion Intelligent autonomous systems in psychiatry Condition monitoring of internal combustion engine Security management of an enterprise network High dimensional neural nets and applications This book is directed to engineers, scientists, professor and the undergraduate/postgraduate students who wish to explore this field further.
Author: Longbing Cao
Publisher: Springer Science & Business Media
ISBN: 1441905227
Category : Computers
Languages : en
Pages : 334
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Book Description
Data Mining and Multi agent Integration aims to re?ect state of the art research and development of agent mining interaction and integration (for short, agent min ing). The book was motivated by increasing interest and work in the agents data min ing, and vice versa. The interaction and integration comes about from the intrinsic challenges faced by agent technology and data mining respectively; for instance, multi agent systems face the problem of enhancing agent learning capability, and avoiding the uncertainty of self organization and intelligence emergence. Data min ing, if integrated into agent systems, can greatly enhance the learning skills of agents, and assist agents with predication of future states, thus initiating follow up action or intervention. The data mining community is now struggling with mining distributed, interactive and heterogeneous data sources. Agents can be used to man age such data sources for data access, monitoring, integration, and pattern merging from the infrastructure, gateway, message passing and pattern delivery perspectives. These two examples illustrate the potential of agent mining in handling challenges in respective communities. There is an excellent opportunity to create innovative, dual agent mining interac tion and integration technology, tools and systems which will deliver results in one new technology.
Author: Vladimir Gorodetsky
Publisher: Springer
ISBN: 3540319328
Category : Computers
Languages : en
Pages : 303
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Book Description
This volume contains the papers presented at the International Workshop Autonomous Intelligent Systems: Agents and Data Mining (AIS-ADM 2005) held in St. Petersburg, Russia, during June 6–8, 2005.
Author: Dominik Ryzko
Publisher: John Wiley & Sons
ISBN: 1119597846
Category : Computers
Languages : en
Pages : 208
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Book Description
Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.
Author: Longbing Cao
Publisher: Springer Science & Business Media
ISBN: 3642276083
Category : Computers
Languages : en
Pages : 368
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Book Description
This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Agents and Data Mining Interaction, ADMI 2011, held in Taipei, Taiwan, in May 2011 in conjunction with AAMAS 2011, the 10th International Joint Conference on Autonomous Agents and Multiagent Systems. The 11 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on agents for data mining; data mining for agents; and agent mining applications.
Author: Longbing Cao
Publisher: Springer
ISBN: 3319202308
Category : Computers
Languages : en
Pages : 125
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Book Description
This book constitutes the thoroughly refereed and revised selected papers from the 10th International Workshop on Agents and Data Mining Interactions, ADMI 2014, held in Paris, France, in May 2014 as satellite workshop of AAMAS 2014, the 13th International Conference on Autonomous Agents and Multiagent Systems. The 11 papers presented were carefully reviewed and selected from numerous submissions for inclusion in this volume. They present current research and engineering results, as well as potential challenges and prospects encountered in the respective communities and the coupling between agents and data mining.
