Q3: Who is concerned with EAs?

EVOLUTIONARY COMPUTATION attracts researchers and people of quite dissimilar disciplines, i.e. EC is a interdisciplinary research field:

Computer scientists

Want to find out about the properties of sub-symbolic information processing with EAs and about learning, i.e. adaptive systems in general.

They also build the hardware necessary to enable future EAs (precursors are already beginning to emerge) to huge real world problems, i.e. the term "massively parallel computation" [HILLIS92], springs to mind.

Engineers

Of many kinds want to exploit the capabilities of EAs on many areas to solve their application, esp. OPTIMIZATION problems.

Roboticists

Want to build MOBOTs (MOBile ROBOTs, i.e. R2D2's and #5's cousins) that navigate through uncertain ENVIRONMENTs, without using built-in "maps". The MOBOTS thus have to adapt to their surroundings, and learn what they can do "move-through-door" and what they can't "move-through-wall" on their own by "trial-and- error".

Cognitive scientists

Might view CFS as a possible apparatus to describe models of thinking and cognitive systems.

Physicists

Use EC hardware, e.g. Hillis' (Thinking Machine Corp.'s) Connection Machine to model real world problems which include thousands of variables, that run "naturally" in parallel, and thus can be modelled more easily and esp. "faster" on a parallel machine, than on a serial "PC" one.

Biologists

Are finding EAs useful when it comes to protein folding and other such bio-computational problems (see Q2).

EAs can also be used to model the behaviour of real POPULATIONs of organisms. Some biologists are hostile to modeling, but an entire community of Population Biologists arose with the 'evolutionary synthesis' of the 1930's created by the polymaths R.A. Fisher, J.B.S. Haldane, and S. Wright. Wright's SELECTION in small populations, thereby avoiding local optima) is of current interest to both biologists and ECers -- populations are naturally parallel.

A good exposition of current population Biology modeling is J. Maynard Smith's text Evolutionary Genetics. Richard Dawkin's Selfish Gene and Extended Phenotype are unparalleled (sic!) prose expositions of evolutionary processes. Rob Collins' papers are excellent parallel GA models of evolutionary processes (available in [ICGA91] and by FTP from ftp://ftp.cognet.ucla.edu/pub/alife/papers/ ).

As fundamental motivation, consider Fisher's comment: "No practical biologist interested in (e.g.) sexual REPRODUCTION would be led to work out the detailed consequences experienced by organisms having three or more sexes; yet what else should [s/]he do if [s/]he wishes to understand why the sexes are, in fact, always two?" (Three sexes would make for even weirder grammar, [s/]he said...)

Chemists

And in particular biochemists and molecular chemists, are interested in problems such as the conformational analysis of molecular clusters and related problems in molecular sciences. The application of GAs to molecular systems has opened an interesting area of research and the number of chemists involved in it increases day-by-day.

Some typical research topics include:

Several papers have been published in journals such as Journal of Computational Chemistry and Journal of Computer-Aided Design.

Some interesting WWW sites related to the applications of GAs to chemistry (or molecular science in general) include:

See also Q2 for applications in biocomputing.

Philosophers

and some other really curious people may also be interested in EC for various reasons.


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Hitch Hiker's Guide to Evolutionary Computation, Issue 9.1, released 12 April 2001
Copyright © 1993-2001 by J. Heitkötter and D. Beasley, all rights reserved.