If you are given the problem, you can learn the parameters by just computing them. For instance, to estimate the parameters of a gaussian, we can compute the mean and variance and shove it in.

There are many different types of uncertainty.

• Outcome Uncertainty: actions may not have known results
• Model Uncertainty: best action in a state may not be known
• State Uncertainty: current state may not be precisely known
• Interaction Uncertainty: interference between models