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Information as Receptive Relation

Tianen Wang Xi Wang

$273

Hardback

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English
Routledge
14 June 2024
This book aims to revolutionize information research by introducing a receptive relation understanding of information, which systematically unveils its fundamental characteristics: created ex nihilo, emergence, reciprocity and shareability.

Through a thorough exploration of organismic and sensory receptivity, the book establishes a mechanistic foundation for understanding the nature of information. It navigates the origins of biological information and leads readers into a new era of information studies. Offering a fresh perspective on the nature of information, it delves into its physical, digital, and ideational encodings, as well as the ideational system built upon them. The book sheds light on critical issues such as quantum manifestation of information and the fundamental laws governing the relationship between information and matter/energy. It also dispels common misconceptions about information and its role in the evolution of information civilization.

The book provides valuable insights into understanding artificial general intelligence and the mysteries of consciousness and life. It will be of interest to researchers and students of information philosophy, information science, and artificial intelligence.

By:   ,
Imprint:   Routledge
Country of Publication:   United Kingdom
Dimensions:   Height: 234mm,  Width: 156mm, 
Weight:   510g
ISBN:   9781032776804
ISBN 10:   1032776803
Pages:   182
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

Tianen Wang is a Professor of Philosophy at Shanghai University with a Ph.D. from Wuhan University. His current research interests concern an integrated philosophical and scientific investigation of information, big data, and artificial intelligence based on systemic research on theories of description and stipulation. Xi Wang is a lecturer at the School of Computer Engineering and Science, Shanghai University. She received her Ph.D. degree from Hosei University, Japan. Her research interests include software engineering and machine learning.

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