According to the No-Free-Lunch Theorems, it is necessary for search
algorithms to incorporate some knowledge of the search space in order to
perform better than random search. Incorporation of a priori
such as expert knowledge, meta-heuristics and human preferences,
and most importantly domain knowledge discovered during evolutionary
search, into evolutionary algorithms has gained increasing interest in
the recent years. However, work on knowledge extraction and incorporation
computation has been carried out from a wide range of research
backgrounds and so far, few efforts have been made to put the diversified
methods under a unified framework.
This special issue attempts to put together the state-of-art and recent advances on knowledge incorporation in evolutionary computation under a systematic and unified framework. Topics include but are not limited to:
Perspective authors should follow the instructions in Information for Authors, see http://www.isye.gatech.edu/ieee-smc/publications/information.html. Electronic submissions in Portable Document Format (PDF) are strongly encouraged. Send all submissions to Dr. Yaochu Jin at yaochu.jin@honda-ri(dot)de.
Guest EditorYaochu Jin