The article discusses how learning processes affect the performance of monetary policy rules in a macroeconomic model. By using estimation algorithms instead of rational expectations, the model can capture the dynamics of agents learning over time. The research shows that while learning can introduce additional complexities, most results from the original model remain valid. This highlights the importance of considering learning processes when analyzing the stability of monetary policy rules in the economy.