The epistemological synthesis of the various theories of evolution, since the first formulation in 1802 with the transmission of the inherited characters by J.B. Lamarck, shows the need for an alternative synthesis to that of Princeton (1947). This new synthesis integrates the scientific models of self-organization developed during the second half of the 20th century based on the laws of physics, thermodynamics, and mathematics with the emergent evolutionary problematics such as self-organized memory. This book shows, how self-organization is integrated in modern evolutionary biology. It is divided in two parts: The first part pays attention to the modern observations in paleontology and biology, which include major theoreticians of the self-organization (d’Arcy Thompson, Henri Bergson, René Thom, Ilya Prigogine). The second part presents different emergent evolutionary models including the sciences of complexity, the non-linear dynamical systems, fractals, attractors, epigenesis, systemics, and mesology with different examples of the sciences of complexity and self-organization as observed in the human lineage, from both internal (embryogenesis-morphogenesis) and external (mesology) viewpoints.

may be complex without being able to be replaced by something »still more simple«. This became evident with the help of computer models of deterministic-recursive systems in which simple mathematical equation systems provide an extremely complex behavior. (2) Irregularity of nature is not treated as an anomaly but becomes the focus of research and thus is declared to be normal. One looks for regularity within irregularity. Non-equilibrium processes are recognized as the source of order and the search for equilibrium is replaced by the search for the dynamics of processes. (3) The classical system-environment model, according to which the adaptation of a system to its environment is controlled externally and according to which the adaptation of the system occurs in the course of a learning process, is replaced by a model of systemic closure. This closure is operational in so far as the effects produced by the system are the causes for the maintenance of systemic organization. If there is sufficient complexity, the systems perform internal self-observation and exert self-control (»Cognition« as understood by Maturana as self-perception and self-limitation, e. g. , that of a cell vis-a. -vis its environment). 22 But any information a system provides on its environment is a system-internal construct. The »reference to the other« is merely a special case of »self-reference«. The social sciences frequently have suffered from the careless way in which scientific ideas and models have been transferred.

The concept of self-organization is at the heart of the theory of complex systems. It describes how order can emerge from disorder in otherwise chaotic nonlinear dynamical systems. This book investigates and surveys the role of self-organization in a wide variety of disciplines. The contributions are written by world-renowned scientists and philosophers at a level that is accessible to nonspecialists.

Non-linear systems behaviours are discussed in this book from the point of new scientific approaches to the interdiscipline nature of the fractal geometry and synergetics. Fractal analysis, synergetics methods and mathematical design are considered according to actual problems of condensed media physics, mechanics, material science and geology.

Self-organized criticality, the spontaneous development of systems to a critical state, is the first general theory of complex systems with a firm mathematical basis. This theory describes how many seemingly desperate aspects of the world, from stock market crashes to mass extinctions, avalanches to solar flares, all share a set of simple, easily described properties. "...a'must read'...Bak writes with such ease and lucidity, and his ideas are so intriguing...essential reading for those interested in complex systems...it will reward a sufficiently skeptical reader." -NATURE "...presents the theory (self-organized criticality) in a form easily absorbed by the non-mathematically inclined reader." -BOSTON BOOK REVIEW "I picture Bak as a kind of scientific musketeer; flamboyant, touchy, full of swagger and ready to join every fray... His book is written with panache. The style is brisk, the content stimulating. I recommend it as a bracing experience." -NEW SCIENTIST

Self-Organization in Sensor and Actor Networks explores self-organization mechanisms and methodologies concerning the efficient coordination between intercommunicating autonomous systems.Self-organization is often referred to as the multitude of algorithms and methods that organise the global behaviour of a system based on inter-system communication. Studies of self-organization in natural systems first took off in the 1960s. In technology, such approaches have become a hot research topic over the last 4-5 years with emphasis upon management and control in communication networks, and especially in resource-constrained sensor and actor networks. In the area of ad hoc networks new solutions have been discovered that imitate the properties of self-organization. Some algorithms for on-demand communication and coordination, including data-centric networking, are well-known examples. Key features include: Detailed treatment of self-organization, mobile sensor and actor networks, coordination between autonomous systems, and bio-inspired networking. Overview of the basic methodologies for self-organization, a comparison to central and hierarchical control, and classification of algorithms and techniques in sensor and actor networks. Explanation of medium access control, ad hoc routing, data-centric networking, synchronization, and task allocation issues. Introduction to swarm intelligence, artificial immune system, molecular information exchange. Numerous examples and application scenarios to illustrate the theory. Self-Organization in Sensor and Actor Networks will prove essential reading for students of computer science and related fields; researchers working in the area of massively distributed systems, sensor networks, self-organization, and bio-inspired networking will also find this reference useful.

This book integrates the theories of complex self-organizing systems with the rich body of discourse and literature developed in what might be called ‘social theory of cities and urbanism’. It uses techniques from dynamical complexity and synergetics to successfully tackle open social science questions.