Dr. Arthur M. Farley is currently conducting research in two areas:
- Artificial Evolution, and
- Algorithmic Graph Theory.
Artificial evolution studies evolution in an abstract, simplified setting, illuminating many of the complexities of environments, individuals, and genetic representations in the hope of uncovering the basic impacts of various processes on the dynamics of evolution. As a field of study, artificial evolution sits between the study of biological evolution and applied evolutionary computation. The study of biological evolution must attempt to model a wide range of natural factors including the complexity of DNA and its chemical reaction with enzymes producing specialized proteins all the way to interactions between individuals and environments. We are considering questions of developmental learning, dominance, and structured populations.
Algorithmic graph theory considers extremal problems on graphs, determining optimal graph structures for given tasks or optimal algorithms on given graph structures. We are considering questions of graphs where distances reflect importance of vertices and which are resilient to certain forms of attack. Substructures that allow efficient group communication are also of interest.