Signals and Boundaries: Building Blocks for Complex Adaptive Systems - Tapa dura

"What is common to cells, rainforests, markets, and language? John Holland demonstrates that each of these complex systems can be analyzed by studying the signals between their evolving parts, the changing boundaries that define these parts, and the coevolution of the signals and the boundaries. The result is a deeper understanding of all complex systems as each application enlightens the others. A remarkable achievement."--Robert Axelrod, author of The Evolution of Cooperation "Complex adaptive systems assume definition as agents arise and organize themselves into specialized units with boundaries and signals that sustain those boundaries, becoming agents themselves in ever-more-complex hierarchies. In his characteristic engaging style, John Holland elucidates the universal organizational principles that characterize hierarchical pattern formation across the spectrum of science."--Simon Levin, Moffett Professor of Biology, Princeton University

Complex adaptive systems (cas), including ecosystems, governments, biological cells, and markets, are characterized by intricate hierarchical arrangements of boundaries and signals. In ecosystems, for example, niches act as semi-permeable boundaries, and smells and visual patterns serve as signals; governments have departmental hierarchies with memoranda acting as signals; and so it is with other cas. Despite a wealth of data and descriptions concerning different cas, there remain many unanswered questions about "steering" these systems. In Signals and Boundaries, John Holland argues that understanding the origin of the intricate signal/border hierarchies of these systems is the key to answering such questions. He develops an overarching framework for comparing and steering cas through the mechanisms that generate their signal/boundary hierarchies. Holland lays out a path for developing the framework that emphasizes agents, niches, theory, and mathematical models. He discusses, among other topics, theory construction; signal-processing agents; networks as representations of signal/boundary interaction; adaptation; recombination and reproduction; the use of tagged urn models (adapted from elementary probability theory) to represent boundary hierarchies; finitely generated systems as a way to tie the models examined into a single framework; the framework itself, illustrated by a simple finitely generated version of the development of a multi-celled organism; and Markov processes.