Knowledge Incorporation in Evolutionary Computation
The basic idea of interactive evolution is to involve a human expert
on-line into the evolution process. During evolution, the human expert selects
one or more individuals that survive and reproduce to form a new generation.
Interactive Evolutionary Computation
However, it would be arduous for human beings to sit in front of the computer
and make endless choices. This entails a method to abstract the knowledge
from the human expert and build a surrogate so that the evolution process can be
carried out freely and automatically. This is also related to evolutionary
computation with approximate fitness functions.
Multiple Objective Optimization Using Fuzzy Preferences
Multiple Objective Optimization (MOO) has received wide attention in evolutionary
design optimization. In many cases, not all objectives are equally important.
A common situation is that "objective A is more important than objective B, and
objective C is equally important as objective D" and so on. In this case, the
preferences expressed in human language need to be translated to numbers
in optimization. To this end, fuzzy preference modeling and fuzzy multiple criteria
decision making can be applied. More importantly, the preferences can be changed interactively during evolution.
Knowledge Incorporation in representation, population initialization
One most direct method for incorporating knowledge into evolutionary computation
is to encode the a prior knowledge in the initial population. In evolutionary
fuzzy rule generation, knowledge can also be incorporated by checking the consistency
between the rules generated by data and those generated by human experts.
Knowledge Incorporation in Recombination and Mutation
Knowledge Incorporation in selection and reproduction
Knowledge Incorporation in Fitness Evaluations
Knowledge Incorporation through Life-time Learning
 Y. Jin (Editor). Knowledge incorporation in evolutionary computation.
Springer, Berlin Heidelberg, 2005
For discussions, please contact Yaochu Jin.