Learning with misspecification in an artificial currency market

Agents evolve their forecast rules over time via a modified genetic algorithm in a simple artificial currency market. These forecast rules can be nonlinearly misspecified. When the misspecification is suppressed, learning tends to be complete. When it is not suppressed, learning can generate persistent exchange rate dynamics.