Evolution and Optimum Seeking

Random Strategies 103
out, a limited life span of all individuals is an important ingredient in such cases (principle
of forgetting).
Two others who have tried to explain brain processes on an evolutionary, at least
selectionist, basis are Edelman (1987) and Conrad (1988). Though their approach has
not yet been embraced by the main stream of neural network research, this mighthappen
in the near future (e.g., Banzhaf and Schmutz, 1992).
An even more general paradigm shift in the eld of arti cial intelligence (AI) has
emerged under the label arti cial life (AL see Langton, 1989, 1994a,b Langton et al.,
1992 Varela and Bourgine, 1992). Whereas Lindenmayer (see Prusinkiewicz and Lindenmayer,
1990) demonstrates the possibility of (re-)creating plant forms by means of
rather simple computer algorithms, the AL community tries to imitate animal behavior
computationally. In most cases the goal is to design \intelligent" robots, sometimes called
knowbots or animats (Meyer and Wilson, 1991 Meyer, 1992 Meyer, Roitblat, and Wilson,
1993).
The attraction of even simple evolutionary models (re-)producing fairly complex behavior
of multi-individual systems simulated on computers is already spreading across
the narrow bounds of computer science as such. New ideas are emerging from evolutionary
computation, not only towards the organization of software development (Huberman,
1988), but also into the eld of economics (e.g., Witt, 1992 Nissen, 1993, 1994) and even
beyond (Schwefel, 1988 Haefner, 1992). It may be questionable whether worthwhile conclusions
from the new ndings can reach as far as that, but ecology at least should be a
eld that could bene t from a consequent use of evolutionary thinking (see Wol , Soeder,
and Drepper, 1988).
Computers have opened a third way of systems analysis aside from the classical mathematical/analytical
and experimental/empirical main roads: i.e., numerical and/or symbolical
simulation experiments. There is some hope that we may learn this way quickly
enough so that we can maintain life on earth before we more or less unconsciously destroy
it. Real evolution always had to deal with unpredictable environmental changes, not only
those resulting from exogenous in uences, but also self-induced endogenous ones. The
landscape is some kind of n-dimensional trampoline, and every good imitation of organic
evolution, whether it be called adaptive or meliorizing, must be able to work properly under
such hard conditions. The multimembered evolution strategy (see Chap. 5, Sect. 5.2)
with limited life span of the individuals ful lls that requirement to some extent.