Modern Big Data Architectures : A Multi-Agent Systems Perspective

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. "This book describes modern concepts and architectures for big data processing and analytics. It shows how data sets are produced and how they can be utilized to bring value in various branches of industry and science. It elaborates on how to apply common computational models and state of the art architectures to accomplish these tasks. Each chapter provides practical examples while describing solutions, which are universal and generic enough to be applicable in a wide variety of use cases. What is unique to this work, is the joint analysis of big data and multi-agent systems, with respect to distributed, intelligent processing of very large data sets. It is argued that we have arrived at the point of convergence of the base concepts of agent, actor, micro-service etc. and we can take the best from both fields in order to build next generation of systems"-- Provided by publisher