Both tasks can be computationally very demanding. For very simple probability models, this approach has been found to be very effective. Many researchers have looked at more sophisticated probability models, using ideas from graphical models. However, for these the computational costs can be high, and much less is known about their effectiveness. The goal of this project is to study whether there is any benefit to model the population using graphical models of probability.
Many search algorithms combine local search with evolutionary search.
For many problems, this results in a very effective algorithm. The latter approach is thereby Darwinian, because acquired traits are not passed to the next generation. There are arguments both ways about the efficiency of each approach, and some empirical studies have been done. The goal of this project is to study this question. This could be done theoretically or through simulations.