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Modern Big Data Architectures - A Multi-Agent Systems Perspective (Hardcover)
Loot Price: R1,074
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Modern Big Data Architectures - A Multi-Agent Systems Perspective (Hardcover)
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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.
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