This study introduces a computational tool to analyze how a population of decision makers communicates and learns to coordinate to attain an equilibrium or a social convention in a two-sided matching game with incomplete information. Genetic algorithms are used in an environment where agents are...

We propose the use of a new technique -- symbolic regression -- as a method for inferring the strategies that are being played by subjects in economic decision-making experiments. We begin by describing symbolic regression and our implementation of this technique using genetic programming. We...

We introduce adaptive learning behavior into a general equilibrium lifecycle economy with capital accumulation. Agents form forecasts of the rate of return to capital assets using least squares autoregressions on past data. We show that, in contrast to the perfect foresight dynamics, a dynamical...