Information and Self-Organization

1. Front Matter

   Pages I-XIV

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2. The Challenge of Complex Systems

   Pages 1-35

3. From the Microscopic to the Macroscopic World ...

   Pages 36-52

4. ... and Back Again: The Maximum Information Principle (MIP)

   Pages 53-64

5. An Example from Physics: Thermodynamics

   Pages 65-68

6. Application of the Maximum Information Principle to Self-Organizing Systems

   Pages 69-73

7. The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns

   Pages 74-80

8. Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points

   Pages 81-114

9. Direct Determination of Lagrange Multipliers

   Pages 115-124

10. Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin-Îto Equations

    Pages 125-134

11. Application to Some Physical Systems

    Pages 135-139

12. Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements

    Pages 140-152

13. Pattern Recognition. Unbiased Guesses of Processes: Explicit Determination of Lagrange Multipliers

    Pages 153-194

14. Information Compression in Cognition: The Interplay between Shannon and Semantic Information

    Pages 195-202

15. Quantum Systems

    Pages 203-215

16. Quantum Information

    Pages 216-221

17. Quantum Computation

    Pages 222-241

18. Concluding Remarks and Outlook

    Pages 242-243

19. Back Matter

    Pages 244-258

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The widespread interest this book has found among professors, scientists and stu­ 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 meet­ 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 Shan­ 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, al­ 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 computa­ tion. The inclusion of these topics is a must for any modern treatise dealing with in­ formation. It becomes more and more evident that the abstract concept of informa­ tion is inseparably tied up with its realizations in the physical world.

• Helium-Atom-Streuung
• Information
• Information Theory
• Quantum information
• REM
• STEM
• Self-Organisation
• Shannon
• Synergetics
• chaos theory
• cognition
• complex system
• complex systems
• entropy
• thermodynamics

From the reviews of the third edition:

"This enlarged edition of Information and Self-Organization addresses the concept of information in depth: ranging ‘from Shannon information, from which all semantics has been exorcised, to the effects of information on receivers and the self-creation of meaning’—that is, toward semantic information … . Nevertheless, both the qualitative lessons and quantitative analysis presented in the book … very useful for artificial life researchers." (Mikhail Prokopenko, Artificial Life, Vol. 15, 2009)

• Institut für Theoretische Physik, Zentrum für Synergetik, Universität Stuttgart, Stuttgart, Germany

  Hermann Haken

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