Society often allocates valuable resources - such as prestigious positions, salaries, or marriage partners - via tournament-like institutions. In such situations, inequality affects incentives to compete and hence has a direct effect on equilibrium choices and hence material outcomes. We...

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes....

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The 'TASP' (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes. We...

We report experiments designed to test the theoretical possibility, first discovered by Shapley (1964), that in some games learning fails to converge to any equilibrium, either in terms of marginal frequencies or of average play. Subjects played repeatedly in fixed pairings one of two 3 ´ 3...

Society often allocates valuable resources - such as prestigious positions, salaries, or marriage partners - via tournament-like institutions. In such situations, inequality affects incentives to compete and hence has a direct effect on equilibrium choices and hence material outcomes. We...

Reinforcement learning and stochastic fictitious play are apparent rivals as models of human learning. They embody quite different assumptions about the processing of information and optimisation. This paper compares their properties and finds that they are far more similar than was thought. In...

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes....

We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The “TASP” (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under a wide class of learning processes. We...