Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010236816 | QH323.5 B55 2010 | Open Access Book | Book | Searching... |
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Summary
Summary
Cellular Automata and Complex Systems: Methods for Modeling Biological Phenomena describes the use of cellular automata to provide important insights into a vast range of physical, biological, social, economic and psychological phenomena. This book presents contemporary research on discrete dynamical systems such as one-dimensional and two-dimensional cellular automata and outlines how these systems can be exploited for artistic purposes, translating their mathematical configurations into music and visual media.
Reviews 1
Choice Review
"Interdisciplinary" can signal either synergetic interaction or interstitial isolation. Cellular automata (CA) can appear to physicists like toy systems of interacting particles; to biologists, like toy ecosystems or organisms; to mathematicians, like potentially complex dynamical systems; to computer scientists, like minimal models of parallel computation; but studied for their own sake, CA generate no more excitement than that associated with recreational mathematics. Disciplines supply methodology--criteria for framing valuable questions and recognizing valid answers. In particular, "model" ought to mean a manageable system that demonstrably captures the essential features of an intrinsically interesting one. The CA studied in this work by Univ. of Calabria (Italy) professors Bilotta (cognitive psychology) and Pantano (mathematical physics) may exhibit "evolution" by "genetic" "mutation" subject to "selection" by "fitness," but no working biologist will recognize testable insights into real biological phenomena. Where S. Wolfram's famous, well-produced A New Kind of Science (CH, Nov'02, 40-1590) stirred controversy with all its pretension but also begrudging admiration, this poorly edited, overblown treatise concerning genetic algorithms for producing CA exhibiting empirical complexity does not inspire. Data better distributed online pad the cookie-cutter chapters. The final chapter on music seems to wander in--and offers nothing to hear (e.g., online or print music notation) for judging the theory. Summing Up: Not recommended. D. V. Feldman University of New Hampshire
