The document discusses using evolutionary algorithms and modeling to understand cooperative behavior in complex systems. It describes how agent behaviors can be evolved using a genetic algorithm to optimize behaviors according to a fitness function. Simulation results show how cooperation can evolve over time in models of problems like the prisoner's dilemma and public goods games under different selection pressures and environment structures. Challenges in the evolutionary modeling approach are also discussed.