Reductive Model of the Conscious Mind

Reductive Model of the Conscious Mind

Indexed In: PsycINFO®
Release Date: August, 2020|Copyright: © 2021 |Pages: 296
DOI: 10.4018/978-1-7998-5653-5
ISBN13: 9781799856535|ISBN10: 1799856534|EISBN13: 9781799856559
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Description & Coverage
Description:

Research on natural and artificial brains is proceeding at a rapid pace. However, the understanding of the essence of consciousness has changed slightly over the millennia, and only the last decade has brought some progress to the area. Scientific ideas emerged that the soul could be a product of the material body and that calculating machines could imitate brain processes. However, the authors of this book reject the previously common dualism—the view that the material and spiritual-psychic processes are separate and require a completely different substance as their foundation.

Reductive Model of the Conscious Mind is a forward-thinking book wherein the authors identify processes that are the essence of conscious thinking and place them in the imagined, simplified structure of cells able to memorize and transmit information in the form of impulses, which they call neurons. The purpose of the study is to explain the essence of consciousness to the degree of development of natural sciences, because only the latter can find a way to embed the concept of the conscious mind in material brains. The book is divided into three parts. Part 1 works to convince readers that the emergence of consciousness does not require detailed knowledge of the structure and morphology of the brain, with the exception of some specific properties of the neural network structure that the authors attempt to point out. Part 2 proves that the biological structure of many natural brains fulfills the necessary conditions for consciousness and intelligent thinking. Similarly, Part 3 shows the ways in which artificial creatures imitating natural brains can meet these conditions, which gives great hopes for building artificially intelligent beings endowed with consciousness. Covering topics that include cognitive architecture, the embodied mind, and machine learning, this book is ideal for cognitive scientists, philosophers of mind, neuroscientists, psychologists, researchers, academicians, and advanced-level students. The book can also help to focus the research of linguists, neurologists, and biophysicists on the biophysical basis of postulated information processing into knowledge structures.

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Editor/Author Biographies

Wiesław Galus received the M.S. degree and Ph.D. degree in solid state physics from the Military University of Technology in Warsaw. He worked in the field of laser radiation detection and modulation at the Institute of Quantum Electronics of the Military University of Technology and the Institute of Plasma Physics and Laser Micro-fusion in Warsaw. He is a co-founder of the high-tech company -Vigo System SA, producing uncooled medium- and far-infrared photon detectors. He is currently involved in the philosophy of mind and modeling natural and artificial brain operation as an independent researcher.

Janusz A. Starzyk received a M.S. degree in applied mathematics, a Ph.D. degree in electrical engineering from the Warsaw University of Technology, Warsaw, Poland, and the Habilitation degree in electrical engineering from the Silesian University of Technology, Gliwice, Poland. He was an Assistant Professor with the Institute of Electronics Fundamentals, Warsaw University of Technology. He spent two years as a post-doctoral fellow and a research engineer at McMaster University, Hamilton, ON, Canada. Since 1991, he has been a Professor of electrical engineering and computer science at Ohio University, Athens, and the Director of Embodied Intelligence Laboratories. Since 2007, he has been the Head of the Information Systems Applications, University of Information Technology and Management, Rzeszow, Poland. His research interests include embodied machine intelligence, motivated goal-driven learning, self-organizing associative spatiotemporal memories, active learning of sensory-motor interactions, machine consciousness, and autonomous robots and avatars.

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