An Introduction to Genetic Algorithms - Boente

Chapter 6: Conclusions and Future Directions
techniques. As was also mentioned in chapter 5, one of the major difficulties is having the time scale of
adaptation for the parameters appropriately match the time scale of adaptation of the individuals in the
population. As far as I know, no theoretical work has been done on this in the GA literature. The development
of such a theory is a very important future direction.
The directions listed above are important both for making GAs more sophisticated problem solvers and for
using them to understand evolutionary systems in nature. The following are some important directions for GA
theory:
Connections with the Mathematical Genetics Literature
The GA theory community has not paid enough attention to what has already been done in the related field of
mathematical genetics, though this is changing to some degree (see, e.g., Booker 1993 and Altenberg 1995).
There is much more to be learned there that is of potential interest to GA theory.
Extension of Statistical Mechanics Approaches
As I said in chapter 4, I think approaches similar to that taken by Prugel−Bennett and Shapiro are promising
for better understanding the behavior of GAs. That is, rather than construct exact mathematical models that in
effect take into account every individual in a population, it is more useful to understand how macroscopic
population structures change as a result of evolution. Ultimately we would like to have a general theory of the
evolution of such macroscopic structures that will predict the effects of changes in parameters and other
details of the GA. There is much more to be mined from the field of statistical mechanics in formulating such
theories.
Identifying and Overcoming Impediments to the Success of GAs
In the case studies and in the theoretical discussion we came across many potential impediments to the
success of GAs, including deception, hitchhiking, symmetry breaking, overfitting, and inadequate sampling.
GA researchers do not yet have anywhere near a complete understanding of the precise effects of these and
other impediments on the performance of GAs, or of the precise conditions under which they come about, or
of how to overcome them if that is possible.
Understanding the Role of Schemas in GAs
As readers of chapter 4 have no doubt gleaned, there is still a controversy in the GA community over the
proper role of "schemas" in understanding GAs. This role must be pinned down and agreed on.
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