  Evolutionary game theory is a mathematical toolkit to analyse the
interactions that an individual agent has in a population and how the
composition of strategies in this population evolves over time. While it can
provide neat solutions to simple problems, in more complicated situations where
assumptions such as infinite population size may be relaxed, deriving analytic
solutions can be intractable. In this short paper, we present a game with
complex interactions and examine how an agent-based model may be used as a
heuristic technique to find evolutionarily stable states.
