Implement adaptive systems for Big Data processing using next-generation concepts

As artificial intelligence technology advances, so does our ability to solve complex problems by analyzing Big Data. Modern Big Data Architectures offers a look into the future of Big Data, underscoring the untapped potential of the multi-agent systems (MAS) view.

Author Dominik Ry¿ko, an international expert on processing massive datasets using distributed AI, shows how multiple autonomous AI "agents" can work collaboratively to solve Big Data problems too complex, too difficult, or too large for a typical monolithic system. Considering how the MAS paradigm can improve our current approaches to Big Data, this book covers:

• Agent-based (and non-agent-based) methods of producing Big Data sets
• Key Big Data applications, from product recommendations to drug discovery
• Traditional and next-generation Big Data architectures
• Data mining, machine learning, and SQL analytics using the MAS approach
• Big Data and agents in cloud computing, fog computing, and Internet of Things

Researchers and practitioners alike in the fields of Big Data, analytics, machine learning, cloud computing, and distributed AI will discover new ideas in Modern Big Data Architectures.