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.