The article explores how different types of agents with varying levels of information can affect equilibrium in a model. When some agents have limited information, the equilibrium can become uncertain even if it would be clear with full information. This can happen because agents with limited information need to figure out missing details, leading to potential multiple outcomes. The researchers applied this concept to a monetary policy scenario involving a central bank making decisions based on an interest rate rule.