Students who complete this unit will demonstrate that they can:

• Characterize the state of the art in learning theory, including its achievements and its shortcomings.
• Describe and explain the use of Markov Decision Processes (MDPs) for making complex decisions.
• Compare and contrast passive and active reinforcement learning.
• Design and implement a MDP solver.
• Design and implement a reinforcement learning agent for an MDP.