Complex systems are ubiquitous, and practically all branches of science ranging from physics through chemistry and biology to economics and sociology have to deal with them. In this book we wish to present concepts and methods for dealing with complex systems from a unifying point of view. Therefore it may be of inter­ est to graduate students, professors and research workers who are concerned with theoretical work in the above-mentioned fields. The basic idea for our unified ap­ proach sterns from that of synergetics. In order to find unifying principles we shall focus our attention on those situations where a complex system changes its macroscopic behavior qualitatively, or in other words, where it changes its macroscopic spatial, temporal or functional structure. Until now, the theory of synergetics has usually begun with a microscopic or mesoscopic description of a complex system. In this book we present an approach which starts out from macroscopic data. In particular we shall treat systems that acquire their new structure without specific interference from the outside; i. e. systems which are self-organizing. The vehicle we shall use is information. Since this word has several quite different meanings, all of which are important for our purpose, we shall discuss its various aspects. These range from Shannon information, from which all semantics has been exorcised, to the effects of information on receivers and the self-creation of meaning.

Inhalt

Contents: The Challenge of Complex Systems.- From the Microscopic to the Macroscopic World ... .- ... and Back Again: The Maximum Information Principle (MIP).- An Example from Physics: Thermodynamics.- Application of the Maximum Information Principle to Self-Organizing Systems.- The Maximum Information Principle for Nonequilibrium Phase Transitions: Determination of Order Parameters, Enslaved Modes, and Emerging Patterns.- Information, Information Gain, and Efficiency of Self-Organizing Systems Close to Their Instability Points.- Direct Determination of Lagrange Multipliers.- Unbiased Modeling of Stochastic Processes: How to Guess Path Integrals, Fokker-Planck Equations and Langevin lto Equations.- Application to Some Physical Systems.- Transitions Between Behavioral Patterns in Biology. An Example: Hand Movements.- Pattern Recognition.- Quantum Systems.- Concluding Remarks and Outlook.- References.- Subject Index.