Thursday, December 22, 2005
Has interest in GAs peaked?
Machine Learning, Etc. has a nice analysis of the time history of a number of machine learning related keywords using Google scholar here. The data for "genetic algorithms" would seem to suggest that interest in GAs has peaked or leveled-off. Is this so, or is the work in "genetic algorithms" now diversifying into a number of other names (genetic programming, EDAs, co-evolution, evolvable hardware, etc.)?
Papers submissions at the GECCO have been largely level since 1999 with an uptick or two over the last two years. My own view is that the field has been taking a breather and has been consolidating the gains of the 90s. As recent progress in competent GAs and supermultiplicative efficiency speedups takes off, I predict that interest will continue at current levels or possibly grow again. Growth will be particularly robust if current work in competent GP can be combined with supermultiplicative efficiency enhancement. (via KaraNagai)
Papers submissions at the GECCO have been largely level since 1999 with an uptick or two over the last two years. My own view is that the field has been taking a breather and has been consolidating the gains of the 90s. As recent progress in competent GAs and supermultiplicative efficiency speedups takes off, I predict that interest will continue at current levels or possibly grow again. Growth will be particularly robust if current work in competent GP can be combined with supermultiplicative efficiency enhancement. (via KaraNagai)
