This thesis evaluates the relative performance of different policies for climate mitigation, when more realistic assumptions are adopted regarding the behavior of polluters. Agent-based modeling is used to explore the interaction amongst heterogeneous agents under bounded rationality. A computational framework is developed to support the development of agent-based models in Python. Three types of policy are compared: a carbon tax, a permit trading market, and direct regulation. Further consideration is given regarding the difference of applying these policies upstream, where fossil fuels are extracted, or downstream, where emissions are caused. Policy impacts are analysed upon multiple evaluation criteria, including effects on emissions, technology adoption, competitive dynamics, prices, economic output, wealth distributions, human needs, and the quality of life.