Computer software is finding its way into more life-critical applications every year. There are problems which can be difficult to be solved by classic monolithic software systems instead of by multi-agent systems (MASs). If analyzing traditional software is considerably complex, it is much more complex to analyze a MAS in which intelligent or emergent behaviors may appear. This book is presented as a significant contribution to the analysis of multi-agent systems or MASs. The presented work introduces the basis for the development of a forensic analysis infrastructure for MAS (i.e., an analysis process performed on previously recorded data of the system run), proposes the use of data mining techniques to discover not explicit knowledge in the logs derived from the forensic analysis, explains analysis techniques based on social network analysis, and provides a qualitative analysis on the basis of the semantically rich information provided by agent communication languages and interaction protocols.
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Emilio Serrano, Juan A. Botía and José M. Cadenas are Ph.D. in Computer Science who currently develop their research activity in the Department of Information and Communications Engineering of the University of Murcia, Spain.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computer software is finding its way into more life-critical applications every year. There are problems which can be difficult to be solved by classic monolithic software systems instead of by multi-agent systems (MASs). If analyzing traditional software is considerably complex, it is much more complex to analyze a MAS in which intelligent or emergent behaviors may appear. This book is presented as a significant contribution to the analysis of multi-agent systems or MASs. The presented work introduces the basis for the development of a forensic analysis infrastructure for MAS (i.e., an analysis process performed on previously recorded data of the system run), proposes the use of data mining techniques to discover not explicit knowledge in the logs derived from the forensic analysis, explains analysis techniques based on social network analysis, and provides a qualitative analysis on the basis of the semantically rich information provided by agent communication languages and interaction protocols. 208 pp. Englisch. Seller Inventory # 9783846543528
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Taschenbuch. Condition: Neu. Advancing the state of the art in the analysis of multi-agent systems | Study and Development of Methods and Tools for Testing, Validation and Verification of Multi-Agent Systems | Emilio Serrano (u. a.) | Taschenbuch | 208 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846543528 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 106733960
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computer software is finding its way into more life-critical applications every year. There are problems which can be difficult to be solved by classic monolithic software systems instead of by multi-agent systems (MASs). If analyzing traditional software is considerably complex, it is much more complex to analyze a MAS in which intelligent or emergent behaviors may appear. This book is presented as a significant contribution to the analysis of multi-agent systems or MASs. The presented work introduces the basis for the development of a forensic analysis infrastructure for MAS (i.e., an analysis process performed on previously recorded data of the system run), proposes the use of data mining techniques to discover not explicit knowledge in the logs derived from the forensic analysis, explains analysis techniques based on social network analysis, and provides a qualitative analysis on the basis of the semantically rich information provided by agent communication languages and interaction protocols.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch. Seller Inventory # 9783846543528
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