Название: Parallel Population and Parallel Human: A Cyber-Physical Social Approach
Автор: Peijun Ye, Fei-Yue Wang
Издательство: Wiley-IEEE Press
Год: 2023
Страниц: 353
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Parallel Population and Parallel HumanProposes a new paradigm to investigate an individual’s cognitive deliberation in dynamic human-machine interactions.

Today, intelligent machines enable people to interact remotely with friends, family, romantic partners, colleagues, competitors, organizations, and others. Virtual reality (VR), augmented reality (AR), artificial intelligence (AI), mobile social media, and other technologies have been driving these interactions to an unprecedented level. As the complexity in system control and management with human participants increases, engineers are facing challenges that arise from the uncertainty of operators or users.

Parallel Population and Parallel A Cyber-Physical Social Approach presents systemic solutions for modeling, analysis, computation, and management of individuals’ cognition and decision-making in human-participated systems, such as the MetaVerse. With a virtual-real behavioral approach that seeks to actively prescribe user behavior through cognitive and dynamic learning, the authors present a parallel population/human model for optimal prescriptive control and management of complex systems that leverages recent advances in artificial intelligence. Throughout the book, the authors address basic theory and methodology for modeling, describe various implementation techniques, highlight potential acceleration technologies, discuss application cases from different fields, and more. In addition, the:

Considers how an individual’s behavior is formed and how to prescribe their behavioral modes
Describes agent-based computation for complex social systems based on a synthetic population from realistic individual groups
Proposes a universal algorithm applicable to a wide range of social organization types
Extends traditional cognitive modeling by utilizing a dynamic approach to investigate cognitive deliberation in highly time-variant tasks
Presents a new method that can be used for both large-scale social systems and real-time human-machine interactions without extensive experiments for modeling

Spark is a state-of-the-art framework for high-performance cloud computing designed to efficiently deal with iterative computational procedures that recursively perform operations over the same data, such as supervised Machine Learning algorithms. It is designed to overcome the deficiency of distributed computing on Hadoop, which is another open-source software platform from Apache for distributed Big Data processing over commodity cluster architectures. As the basis of Spark, Hadoop is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

Different from the traditional solution for big data processing where high-performance servers with large memories and advanced CPU/GPUs are resorted to, the basic idea of Hadoop is to construct a cluster that can rival servers using cheap and easily available machines. Such advantage from cost and convenience of system deployment have expanded its application scenarios especially for small and medium corporations with limited budgets. Hadoop has three main components: (i) a Hadoop distributed file system (HDFS) with high-throughput data access; (ii) a MapReduce programming model that separates data processing in mapping for performing data operations locally, shuffling for data redistribution over the network and reduction for data summarization; and (iii) a cluster manager (YARN) in surveillance of the available computing resources and job scheduling.

Parallel Population and Parallel A Cyber-Physical Social Approach is a must-read for researchers, engineers, scientists, professionals, and graduate students who work on systems engineering, human-machine interaction, cognitive computing, and Artificial Intelligence.




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