Grant: Discovery Grants Program - Individual

The goal of the research proposed here is to move from earlier very abstract and simplified EC models, closer to realistic models of natural evolution implemented in computational systems, in other words, in the direction of ""computational evolution"". To this end, a number of basic assumptions of established evolutionary algorithms will be subjected to critical revision. In addition, new concepts of molecular and evolutionary biology not known at the time of the design of these algorithms will be incorporated. While the set of those concepts is virtually endless, my focus for the next five years is on the following topics: (i) epigenetic interactions that allow a genome to reorganize in response to cues from its environment. This is an extremely important concept, notably with respect to the reinforced connection between evolution and development in biology. The inclusion of epigenetic mechanisms in algorithms will happen through the addition of a further layer of control signals for artificial regulatory networks. This constitutes a new way of allowing interactions between an algorithmic genome and its environment. (ii) The evolution of cooperation and its contribution to evolutionary transitions. While earlier models studied two-level systems, in this research we shall study multi-level selection and the benefits to be gained from adapting the size of groups and hierarchies to the problem that is to be solved by evolution. Substantial efficiency gains are expected from these approaches, since they address one of the key problems evolutionary algorithms, and Genetic Programming in particular: scalability. (iii) The emergence of novelty in both biological and computational environments. Novelty and the associated phenomenon of innovation is a central tenet in Darwinian thought. Without the invention of new devices neither nature nor computing reap the full benefits of evolution. Here, we shall examine the mechanisms by which novelty is produced in natural settings, for example by gene duplication in genomes, and seek to transfer recipes into computational systems.