Information and Self-Organization: A Macroscopic Approach to Complex Systems (Springer Series in Synergetics)
β Scribed by Hermann Haken
- Publisher
- Springer
- Year
- 2006
- Tongue
- English
- Leaves
- 272
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The widespread interest this book has found among professors, scientists and stuΒ dents working in a variety of fields has made a new edition necessary. I have used this opportunity to add three new chapters on recent developments. One of the most fascinating fields of modern science is cognitive science which has become a meetΒ ing place of many disciplines ranging from mathematics over physics and computer science to psychology. Here, one of the important links between these fields is the concept of information which, however, appears in various disguises, be it as ShanΒ non information or as semantic information (or as something still different). So far, meaning seemed to be exorcised from Shannon information, whereas meaning plays a central role in semantic (or as it is sometimes called "pragmatic") information. In the new chapter 13 it will be shown, however, that there is an important interplay between Shannon and semantic information and that, in particular, the latter plays a decisive role in the fixation of Shannon information and, in cognitive processes, alΒ lows a drastic reduction of that information. A second, equally fascinating and rapidly developing field for mathematicians, computer scientists and physicists is quantum information and quantum computaΒ tion. The inclusion of these topics is a must for any modern treatise dealing with inΒ formation. It becomes more and more evident that the abstract concept of informaΒ tion is inseparably tied up with its realizations in the physical world.
π SIMILAR VOLUMES
<p><P>This book presents the concepts needed to deal with self-organizing complex systems from a unifying point of view that uses macroscopic data. The various meanings of the concept "information" are discussed and a general formulation of the maximum information (entropy) principle is used. With t