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Multi Agent Systems for Artificial Life Domain: Using Multi Agent system for modeling and simulation of the anticipation behavior and its application in real life domain - Softcover

 
9783838345901: Multi Agent Systems for Artificial Life Domain: Using Multi Agent system for modeling and simulation of the anticipation behavior and its application in real life domain

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In this work, I focus on the use of Anticipation in Multi Agent Systems (MAS), particularly on a preventive anticipation that consists of anticipating undesirable future situations in order to avoid them. In this thesis designed architecture is intended for intelligent autonomous agents that should behave in a complex Artificial Life (ALife) like environment. The primary motivation behind this research was to propose and integrate Anticipation Approaches in a designed simulator. I implemented 3 different types of Machine Learning Algorithms in my Anticipatory Agent System (Anticipator) to see which one gives the most promising results. (Markov Chain, Neural Net and Genetics Programming). After I included an Adaptation Behaviour Block in my (NMAS) system - it has been solved an Adaptation Anticipatory Multi Agent System (A2MAS). Finally, I suggested a concrete approach to a communication among agents in a system Round Contract (RCont) based on principles of the FIPA Contract Net Protocol. In the end, I applied designed systems with anticipation in daily life applications. One of the most useful applications in this area is a Smart Home project especially for Power Management.

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  • PublisherLAP Lambert Academic Publishing
  • Publication date2010
  • ISBN 10 3838345908
  • ISBN 13 9783838345901
  • BindingPaperback
  • LanguageEnglish
  • Number of pages172

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Ahmed Elmahalawy
ISBN 10: 3838345908 ISBN 13: 9783838345901
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this work, I focus on the use of Anticipation in Multi Agent Systems (MAS), particularly on a preventive anticipation that consists of anticipating undesirable future situations in order to avoid them. In this thesis designed architecture is intended for intelligent autonomous agents that should behave in a complex Artificial Life (ALife) like environment. The primary motivation behind this research was to propose and integrate Anticipation Approaches in a designed simulator. I implemented 3 different types of Machine Learning Algorithms in my Anticipatory Agent System (Anticipator) to see which one gives the most promising results. (Markov Chain, Neural Net and Genetics Programming). After I included an Adaptation Behaviour Block in my (NMAS) system - it has been solved an Adaptation Anticipatory Multi Agent System (A2MAS). Finally, I suggested a concrete approach to a communication among agents in a system Round Contract (RCont) based on principles of the FIPA Contract Net Protocol. In the end, I applied designed systems with anticipation in daily life applications. One of the most useful applications in this area is a Smart Home project especially for Power Management. 172 pp. Englisch. Seller Inventory # 9783838345901

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Elmahalawy AhmedAhmed M. Elmahalawy was born in Benha, Egypt and went to the Menoufia University. He had his BSc. degree in 1995 and his MSc. in 2001 and then worked as assistance lecture in Faculty of Electronic Engineering (FEE). H. Seller Inventory # 5415033

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Ahmed Elmahalawy
Published by LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838345908 ISBN 13: 9783838345901
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this work, I focus on the use of Anticipation in Multi Agent Systems (MAS), particularly on a preventive anticipation that consists of anticipating undesirable future situations in order to avoid them. In this thesis designed architecture is intended for intelligent autonomous agents that should behave in a complex Artificial Life (ALife) like environment. The primary motivation behind this research was to propose and integrate Anticipation Approaches in a designed simulator. I implemented 3 different types of Machine Learning Algorithms in my Anticipatory Agent System (Anticipator) to see which one gives the most promising results. (Markov Chain, Neural Net and Genetics Programming). After I included an Adaptation Behaviour Block in my (NMAS) system - it has been solved an Adaptation Anticipatory Multi Agent System (A2MAS). Finally, I suggested a concrete approach to a communication among agents in a system Round Contract (RCont) based on principles of the FIPA Contract Net Protocol. In the end, I applied designed systems with anticipation in daily life applications. One of the most useful applications in this area is a Smart Home project especially for Power Management. Seller Inventory # 9783838345901

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