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This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
Distributed artificial intelligence --- Bayesian statistical decision theory --- Intelligent agents (Computer software) --- Intelligence artificielle répartie --- Statistique bayésienne --- Agents intelligents (logiciels) --- Data processing --- Informatique --- Information Technology --- Computer Science (Hardware & Networks) --- Distributed artificial intelligence. --- Intelligent agents (Computer software). --- Computer Science --- Engineering & Applied Sciences --- Data processing. --- Intelligence artificielle répartie --- Statistique bayésienne --- Agents, Autonomous (Computer software) --- Agents, Cognitive (Computer software) --- Agents, Intelligent (Computer software) --- Assistants, Cognitive (Computer software) --- Assistants, Intelligent software --- Autonomous agents (Computer software) --- Cognitive agents (Computer software) --- Cognitive assistants (Computer software) --- IAs (Computer software) --- Intelligent agent software --- Intelligent software agents --- Intelligent software assistants --- Software agents (Computer software) --- Special agents (Computer software) --- Bayes' solution --- Bayesian analysis --- DAI (Artificial intelligence) --- Distributed AI (Artificial intelligence) --- Artificial intelligence --- Statistical decision --- Computer programs --- E-books --- Multiagent systems. --- Agent-based model (Computer software) --- MASs (Multiagent systems) --- Multi-agent systems --- Systems, Multiagent
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Sensor and Ad-Hoc Networks: Theoretical and Algorithmic Aspects contains an analysis of various important networking problems and brings together recent trends and emerging works in the areas of sensor and ad-hoc networks. This book identifies the areas that are in need of special attention and presents recent research findings. The book features valuable discussions of relevant concepts that examine the various approaches which define emerging theoretical and algorithmic aspects of sensor and ad-hoc networks. The chapters are written by the leading national and international researchers and professionals in the field. Each chapter represents the state-of-the-art research and includes several seminal contributions on such topics as network coverage, detectability, integration, energy efficiency and routing. Sensor and Ad-Hoc Networks: Theoretical and Algorithmic Aspects is a useful reference for researchers, academics, graduate students, and industry professionals in the field of sensor and ad-hoc networks. Some of the works in this book have been supported by the National Science Foundation.
Engineering. --- Communications Engineering, Networks. --- Computer Communication Networks. --- Signal, Image and Speech Processing. --- Electrical Engineering. --- Computer engineering. --- Telecommunication. --- Ingénierie --- Réseaux d'ordinateurs --- Ordinateurs --- Télécommunications --- Conception et construction --- Ad hoc networks (Computer networks). --- Sensor networks. --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Telecommunications --- Electrical Engineering --- Ad hoc networks (Computer networks) --- Computer algorithms. --- MANETs (Computer networks) --- Mobile ad hoc networks --- Wireless ad hoc networks --- Networks, Sensor --- Computers --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Communication --- Information theory --- Telecommuting --- Design and construction --- Algorithms --- Computer networks --- Wireless communication systems --- Detectors --- Context-aware computing --- Multisensor data fusion --- Electrical engineering. --- Computer communication systems. --- Signal processing. --- Image processing. --- Speech processing systems. --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Electric engineering --- Engineering --- Computational linguistics --- Modulation theory --- Oral communication --- Speech --- Singing voice synthesizers --- Distributed processing
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