The article discusses how to solve complex problems in uncertain systems using Approximate Dynamic Programming (ADP) methods. These methods help find good solutions even when the system has a large number of possible states. The researchers developed new ADP schemes called Approximate Q Iteration (AQI) and Variational Approximate Q Iteration (VAQI) to handle these challenges. These methods are proven to be effective and provide a bound on the performance of the sub-optimal policy. The Approximate Linear Program (ALP) uses linear function approximation to guarantee good performance in solving these problems.