It is now nearly half a century since the establishment of game theory as a mechanism for studying evolution. While the primary application of this work has been at the population and species level, the gene's-eye view of evolution was postulated only shortly after evolutionary game theory itself. However, an experimental or empirical approach to the gene's-eye view has not been well developed, primarily due to the challenges associated with measuring how genes act as agents over the course of evolution, with the first mathematical theory describing this perspective only published in 2011. Major advances in our understanding of the core tenets of genetics and biochemistry over the last few decades are providing the data needed to calibrate the gene's-eye approach, and high-throughput sequencing technologies promise to provide even more such data.
In this talk I will present GAME (Gene-Agent Modelling of Evolution), a software package designed for agent-based modelling of evolution from the gene perspective. This model provides a simulation of changes to the value and fitness of individual genes in a population of organisms over time. I will present preliminary results regarding the impacts of mutation and allelic diversity over time, testing the hypothesis that greater allelic diversity at a locus results in greater fitness for that locus.