Biologically-inspired computing

Biologically-inspired computing (also bio-inspired computing) is a field of study that loosely knits together subfields related to the topics of connectionism, collective intelligence and emergence. It is often closely related to the field of artificial intelligence, as many of its pursuits can be linked to machine learning. It relies heavily on the fields of biology, computer science and mathematics. Briefly put, it is the use of computers to model nature, and simultaneously the study of nature to improve the usage of computers.

=Areas of research=

Some areas of study encompassed under the canon of biologically-inspired computing, and their biological counterparts:

*genetic algorithms ↔ evolution *biodegradability prediction ↔ biodegradation *cellular automata ↔ life *emergence ↔ ants, termites, bees, etc *neural networks ↔ the brain *artificial life ↔ life *artificial immune systems ↔ immune system *rendering (computer graphics) ↔ patterning and rendering of animal skins, bird feathers, mollusk shells and bacterial colonies *lindenmayer systems ↔ plant structures *P system ↔ intra-Cell_membrane Molecular_biology processes in the Cell_(biology) *Excitable medium ↔ Wildfires, the Audience wave, Tachycardia, etc

=Bio-inspired computing and AI=

One way in which bio-inspired computing differs from artificial intelligence (AI) is in how it takes a more evolutionary approach to learning, as opposed to the what could be described as s).

Natural evolution is a good analogy to this method–the rules of evolution (selection, recombination/reproduction, mutation and more recently transposition (genetics)) are in principle simple rules, yet over thousands of years have produced remarkably complex organisms. A similar technique is used in genetic algorithms.

=Related articles=

Artificial life

Artificial neural network

Biomimetics

Bioinformatics

Connectionism

Fuzzy logic

Gerald Edelman

Janine Benyus

Mathematical biology

Mathematical model

Olaf Sporns

=Recommended reading=

(the following are presented in ascending order of complexity and depth, with those new to the field suggested to start from the top)

Emergence: The Connected Lives of Ants, Brains, Cities and Software , Steven Johnson.

Dr. Dobb s Journal , Apr-1991. (Issue theme: Biocomputing)

Turtles, Termites and Traffic Jams , Mitchel Resnick.

Understanding Nonlinear Dynamics , Daniel Kaplan and Leon Glass.

[http://mitpress.mit.edu/books/FLAOH/cbnhtml/home.html The Computational Beauty of Nature] , [http://flakenstein.net/ Gary William Flake]. MIT Press. 1998, hardcover ed.; 2000, paperback ed. An in-depth discussion of many of the topics and underlying themes of bio-inspired computing.

=See also=

*Cognitive modeling *Cognitive architecture *Cognitive science *Emergent AI

=External links=

*[http://www.cogs.susx.ac.uk/users/ezequiel/alife-page/development.html ALife Project in Sussex]