Recently I have taken an interest in combining evolution techniques with learning.  I think an interesting area of research, that not a lot of people are looking into, is to evolve neural network structures, and apply learning techniques to optimise weights.  So far, all the experiments I have done is based on Darwinian evolution, where the next generation takes nothing learned in the life of the current generation of agents.  But what if we can have the agents learn something in their lifetime to be better at their task, and share that learning, in the form of a more fine tuned weight parameters, with their offsprings?