  To investigate the origin of cooperative behaviors, we developed an
evolutionary model of sequential strategies and tested our model with computer
simulations. The sequential strategies represented by stochastic machines were
evaluated through games of Iterated Prisoner's Dilemma (IPD) with other agents
in the population, allowing co-evolution to occur. We expanded upon past works
by proposing a novel mechanism to mutate stochastic Moore machines that enables
a richer class of machines to be evolved. These machines were then subjected to
various selection mechanisms and the resulting evolved strategies were
analyzed. We found that cooperation can indeed emerge spontaneously in evolving
populations playing iterated PD, specifically in the form of trigger
strategies. In addition, we found that the resulting populations converged to
evolutionarily stable states and were resilient towards mutation. In order to
test the generalizability of our proposed mutation mechanism and simulation
approach, we also evolved the machines to play other games such as Chicken,
Stag Hunt, and Battle, and obtained strategies that perform as well as mixed
strategies in Nash Equilibrium.
