Creativity in Complex Systems
One of the most attractive features of complex evolutionary
systems is their creativity: novel solutions to difficult problems emerge
spontaneously. Evolutionary arms races illustrate this phenomenon particularly
well. Although computer models have been developed for many complex systems,
very few that exhibit the open-ended creativity of evolutionary arms races.
We argue that the primary reason for this lack of creativity
is that the features upon which creativity is typically built exist at a
level below that of the issues that the model was intended to examine. For
example, for a toxin and anti-toxin to evolve (as in an evolutionary arms
race) in a computer model, the biochemical mechanisms that the toxin effects
must be built into the model in advance. But normally those mechanisms are
at a level significantly below that which the model was intended to examine,
which is the external interaction among entities.
An evolutionary arms race is creative precisely because
it exploits features of entities that were not anticipated as being used
in the way the arms race found to use them. Evolutionary creativity is difficult
to model because the complexity of the mechanisms that would have to be built
into the model in advance is typically overwhelmingly large.
We argue that the only feasible alternative to building
inordinately complex physical and chemical details into a model in advance,
details which are unlikely to be used in any event, is to allow the evolutionary
process to evolve mechanisms that are open ended in some meaningful way.
This differs from many evolutionary models in which (a) parameters are allowed
to vary but (b) the basic functioning of the agents in the models are set
in advance. Genetic programming is one framework that allows such open ended
evolution. So far its use has been limited primarily to problem solving in
the tradition of genetic algorithms rather than in co-evolutionary agent
based models.
Russ Abbott
California State University, Los Angeles
Department of Computer Science
rabbott@calstatela.edu