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A Computational Intelligence Paradigm: A Biologically Inspired Artificial Immunity for a Multi-Agent Mobile Robotics System - Softcover
Inhaltsangabe
This book aims at improving the working of Robots using natural phenomenon that exist around us, one such technique is the Natural Immune System. The biological immune system is a great source of inspiration for developing intelligent problem-solving techniques. Like other biologically motivated approaches, Artificial Immune System (AIS) is also a rapidly emerging field. It is used in pattern recognition, fault detection, computer security and a variety of other applications in science and engineering. It is expected that Artificial Immune System will be able to detect faults and make recommendations to a high-level control system about corrective action ? similar to that of a human adaptive Immune System which keep the body healthy. Most of the research carried out so far is based either on the innate or adaptive characteristics of the immune system, this book attempts to combine them together to imitate the natural immune system and applied on a Multi-Robot Scenario. Very few work using AIS as an approach to multi-robot environment has been carried out so far. A case based experiment on how the robots interact with each other to exist in harmony is presented in this text.
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Reseña del editor
This book aims at improving the working of Robots using natural phenomenon that exist around us, one such technique is the Natural Immune System. The biological immune system is a great source of inspiration for developing intelligent problem-solving techniques. Like other biologically motivated approaches, Artificial Immune System (AIS) is also a rapidly emerging field. It is used in pattern recognition, fault detection, computer security and a variety of other applications in science and engineering. It is expected that Artificial Immune System will be able to detect faults and make recommendations to a high-level control system about corrective action - similar to that of a human adaptive Immune System which keep the body healthy. Most of the research carried out so far is based either on the innate or adaptive characteristics of the immune system, this book attempts to combine them together to imitate the natural immune system and applied on a Multi-Robot Scenario. Very few work using AIS as an approach to multi-robot environment has been carried out so far. A case based experiment on how the robots interact with each other to exist in harmony is presented in this text.
Biografía del autor
Tejbanta Chingtham received his B.Tech (CSE)from B.U Coimbatore & M.Tech (CSE) from IIT Guwahati and PhD from BIT,Mesra. He is MIEEE, MIAENG & MIACSIT and has served as Technical Committee Members of Various Journals & Conferences. His areas of interest are Artificial Immune System, Natural Computing, Evolutionary Computation & Mobile Robotics
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A Computational Intelligence Paradigm
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843356696
ISBN 13: 9783843356695
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chingtham Tejbanta SinghTejbanta Chingtham received his B.Tech (CSE)from B.U Coimbatore & M.Tech (CSE) from IIT Guwahati and PhD from BIT,Mesra. He is MIEEE, MIAENG & MIACSIT and has served as Technical Committee Members of Various J. Bestandsnummer des Verkäufers 5465664
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A Computational Intelligence Paradigm : A Biologically Inspired Artificial Immunity for a Multi-Agent Mobile Robotics System
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843356696
ISBN 13: 9783843356695
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims at improving the working of Robots using natural phenomenon that exist around us, one such technique is the Natural Immune System. The biological immune system is a great source of inspiration for developing intelligent problem-solving techniques. Like other biologically motivated approaches, Artificial Immune System (AIS) is also a rapidly emerging field. It is used in pattern recognition, fault detection, computer security and a variety of other applications in science and engineering. It is expected that Artificial Immune System will be able to detect faults and make recommendations to a high-level control system about corrective action similar to that of a human adaptive Immune System which keep the body healthy. Most of the research carried out so far is based either on the innate or adaptive characteristics of the immune system, this book attempts to combine them together to imitate the natural immune system and applied on a Multi-Robot Scenario. Very few work using AIS as an approach to multi-robot environment has been carried out so far. A case based experiment on how the robots interact with each other to exist in harmony is presented in this text. Bestandsnummer des Verkäufers 9783843356695
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A Computational Intelligence Paradigm
Verlag:
LAP LAMBERT Academic Publishing Nov 2010, 2010
ISBN 10: 3843356696
ISBN 13: 9783843356695
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at improving the working of Robots using natural phenomenon that exist around us, one such technique is the Natural Immune System. The biological immune system is a great source of inspiration for developing intelligent problem-solving techniques. Like other biologically motivated approaches, Artificial Immune System (AIS) is also a rapidly emerging field. It is used in pattern recognition, fault detection, computer security and a variety of other applications in science and engineering. It is expected that Artificial Immune System will be able to detect faults and make recommendations to a high-level control system about corrective action similar to that of a human adaptive Immune System which keep the body healthy. Most of the research carried out so far is based either on the innate or adaptive characteristics of the immune system, this book attempts to combine them together to imitate the natural immune system and applied on a Multi-Robot Scenario. Very few work using AIS as an approach to multi-robot environment has been carried out so far. A case based experiment on how the robots interact with each other to exist in harmony is presented in this text. 60 pp. Englisch. Bestandsnummer des Verkäufers 9783843356695
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A Computational Intelligence Paradigm
Verlag:
LAP LAMBERT Academic Publishing Nov 2010, 2010
ISBN 10: 3843356696
ISBN 13: 9783843356695
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -This book aims at improving the working of Robots using natural phenomenon that exist around us, one such technique is the Natural Immune System. The biological immune system is a great source of inspiration for developing intelligent problem-solving techniques. Like other biologically motivated approaches, Artificial Immune System (AIS) is also a rapidly emerging field. It is used in pattern recognition, fault detection, computer security and a variety of other applications in science and engineering. It is expected that Artificial Immune System will be able to detect faults and make recommendations to a high-level control system about corrective action ¿ similar to that of a human adaptive Immune System which keep the body healthy. Most of the research carried out so far is based either on the innate or adaptive characteristics of the immune system, this book attempts to combine them together to imitate the natural immune system and applied on a Multi-Robot Scenario. Very few work using AIS as an approach to multi-robot environment has been carried out so far. A case based experiment on how the robots interact with each other to exist in harmony is presented in this text.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch. Bestandsnummer des Verkäufers 9783843356695
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