Assembles the concepts and tools for analyzing complex systems in a wide range of fields
Edited by renowned encyclopedia editor Robert A. Meyers
Appeals to undergraduates, researchers and practitioners
Reflects the real world by integrating complexity with the deterministic equations and concepts that define matter, energy, and the four forces identified in nature
Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other natural disasters; the dynamics of turbulent flows; lasers or fluids in physics, microprocessor design; macromolecular assembly in chemistry and biophysics; brain functions in cognitive neuroscience; climate change; ecosystem management; traffic management; and business cycles. All these seemingly quite different kinds of structure formation have a number of important features and underlying structures in common. These deep structural similarities can be exploited to transfer analytical methods and understanding from one field to another. This unique work will extend the influence of complexity and system science to a much wider audience than has been possible to date.
Written for:
Undergraduate and graduate students in all fields, researchers in academia and government laboratories, technical professionals and managers in industries such as pharmaceuticals, computer hardware and software, aerospace, and telecommunications, financial analysts, and infrastructure managers
Keywords:
Agent Based Modeling
Cellular Automata
Complex Networks
Computational Nanoscience
Ecological Complexity
Ergodic Theory
Fractals and Multifractals
Game Theory
Granular Computing
Graph theory
Intelligent Systems
Perturbation Theory
Quantum Information Science
System Dynamics
Traffic Management
chaos and complexity
climate modeling
complex systems
complexity theory
dynamical systems
fuzzy theory systems
nonlinear systems
soft computing
stochastic processes
synergetics
synergetics and self-organization
systems biology
systems science