 The third prominent model of norm emergence comes from Brian Skyrms (1996, 2004) and Jason Alexander (2007). In this approach, two different features are emphasized: relatively simple cognitive processes and structured interactions. Both have explored a variety of games (such as the prisoner’s dilemma, the stag hunt, divide the dollar, and the ultimatum game) as exemplars of situations that offer the possibility of the emergence of a moral norm. Though Skyrms occasionally uses the replicator dynamic, both tend to emphasize simpler mechanisms in an agent-based learning context. In particular, learning rules like “imitate the best” or best response are used, as they are much less cognitively demanding. Alexander justifies the use of these simpler rules on the grounds that, rather than fully rational agents, we are cognitively limited beings who rely on fairly simple heuristics for our decision-making. Rules like imitation are extremely simple to follow. Best response requires a bit more cognitive sophistication, but is still simpler than a fully Bayesian model with unlimited memory and computational power. These simpler learning rules provide the same function as the replicator dynamic: in between rounds of play, agents rely on their learning rule to decide what strategy to employ. Note that both Skyrms and Alexander tend to treat norms as single strategies.