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.

提供關於大數據和多智能體系統的最新分析

大數據一詞指的是數據集過大或過於複雜，傳統的數據處理軟件無法應對。隨著邊緣計算和物聯網等新概念的普及，這些數據的生產、處理和消費變得越來越分散。因此，應用程序越來越需要能夠共同工作的多個智能體。多智能體系統（MAS）是一種自組織的計算機系統，由多個智能體相互作用以解決超出個體能力範圍的問題。《現代大數據架構》探討了大數據處理和分析的現代概念和架構。

這本獨特且最新的專著提供了大數據和多智能體系統的聯合分析，重點放在分散式、智能處理非常大的數據集上。每一章節都包含實際例子和詳細解決方案，適用於各種應用。作者是國際知名的大數據和分散式人工智能專家，展示了代理、演員和微服務等基本概念已達到匯聚點的情況，通過將該領域的最佳方面納入下一代系統的構建中。本書：

- 說明數據集的生成方式以及如何在工業和科學的各個領域中應用
- 解釋如何應用常見的計算模型和最先進的架構來處理大數據任務
- 討論人工智能在當前和新興大數據應用中的應用

《現代大數據架構：多智能體系統的視角》是數據科學專業人士和從事大數據分析、機器學習和人工智能的學生的及時重要資源。

Dominik Ryżko is an Assistant Professor at the Institute of Computer Science at Warsaw University of Technology. His research interests include Big Data and Distributed Artificial Intelligence. He is widely published, serves on program committees at international conferences, and is Vice President of artificial intelligence and analytics at Adform, a global ad-tech platform provider. He also spent three years at Allegro Group as the Chief Data Scientist where he oversaw Data Science activities, design and methodology of experiments, and model building.

Dominik Ryżko是華沙科技大學計算機科學研究所的助理教授。他的研究興趣包括大數據和分散式人工智能。他在國際會議上廣泛發表論文，並擔任程序委員會成員。他還是全球廣告技術平台提供商Adform的人工智能和分析副總裁。他曾在Allegro Group擔任三年的首席數據科學家，負責監督數據科學活動、實驗設計和方法論以及模型建立。