Signals and Boundaries

Building Blocks for Complex Adaptive Systems

MIT Press

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.

Autoren/Hrsg.

Holland, John H.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Über Autor(innen)

Holland, John H.
John H. Holland is Professor of Psychology and Professor of Computer Science and
Engineering at the University of Michigan; he is also Trustee and External Professor
at the Santa Fe Institute. He is the author of Hidden Order: How Adaptation
Builds Complexity and other books.