hotel market to determine the effects of different regulatory practices [@suzuki2010] and how overcapacity can be used to deter competition [@conlin06]. As a general theme, the econometricians are interested in the intentions that guide behavior. That is, the observed behavior is considered to be the truth and the decision-making framework used by the producers and consumers is known [*a priori*]{}.

The decision theory community is interested in human behavior on a more individual level. They, too, note that out-of-the-box game theory fails to explain how people act in many scenarios. As opposed to viewing this as a flaw in the theories, they focus on both how to alter the games that model our interactions in addition to devising human-like decision-making algorithms. The former can be achieved through modifications to the players’ utility functions, which are known [*a priori*]{}, to incorporate notions such as risk aversion and spite [@myers60; @erev2008]. latter approaches often tweak learning algorithms by integrating memory limitations or emphasizing recent or surprising observations [@camerer1999; @erev2005].

the Iterative Weighting and Sampling algorithm (I-SAW) is more likely to choose the action with the highest estimated utility, but recent observations are weighted more highly and, in the absence of a surprising 