Game theory has become an indispensable tool in the analysis of strategic interactions between people, groups, and nations. It rests on Nash equilibrium as its central concept. In a Nash equilibrium, (1) each player?s action is best, given his or her beliefs over others? actions and (2) those beliefs are correct. However, even under the idealized conditions of laboratory experiments, there are systematic deviations from the predictions of classical game theory. That this is true for even the simplest of games suggests the need to augment the standard theory to predict behavior in more realistic games with policy relevance, such as those used to model firms? decisions to enter markets or countries designing competing trade policies. To reconcile theory with experimental data, this research proposes generalizations of Nash equilibrium that replace conditions (1) and (2) with conditions that allow for players to make mistakes in taking actions and forming beliefs. By collecting experimental data in the laboratory from many simple games, theoretical predictions will be tested and model performance will be assessed. The results will provide a better understanding of how people, organizations, and nations interacting strategically. Better understanding can then translate into better policy-making, more carefully targeted, and more effective in its results.
