A complex system often must navigate a volatile environment populated with similar complex systems. In this chapter, game theory is introduced as a framework for developing and executing strategies that work in changing environments where many agents share a limited resource. Zero-sum games are explored in the context of game trees, the minimax algorithm, and rational players. Emergent and infinite games are also touched upon. Most of the focus is placed on non-zero-sum games. The prisoner’s dilemma is introduced using a payoff matrix but expanding to include other types of games. Repeated games as a pathway to the evolution of cooperation are covered as well as multiplayer games, fitness functions, and landscapes, diversity around a fitness peak, and how dynamic fitness can lead to the Red Queen effect. Direct and indirect forms of reciprocity, various forms of altruism, and levels of symbiosis are also covered. Other topics addressed are genetic algorithms and evolutionary computing, bounded rationality, intuition, and the role of emotions in decision-making. Examples are drawn from the dynamics between parents and their children, social, evolutionary, immune, geopolitical, economic, and technological systems. The chapter concludes with questions for either reflection or group discussion as well as resources for further exploration.