Activity: MDP Knowledge Quiz

Objective: To evaluate students’ understanding of Markov Decision Processes (MDPs) and their key concepts.

Instructions: 1. Divide the students into small groups or pairs. 2. Provide each group with a set of questions related to MDPs. 3. Allocate a specific time limit for the activity (e.g., 20 minutes). 4. Instruct the students to discuss and answer the questions collectively within their groups. 5. Encourage students to explain their reasoning and discuss any disagreements or uncertainties. 6. After the allocated time, gather the groups together for a class discussion. 7. Ask each group to share their answers and reasoning for each question. 8. Facilitate a discussion among the students, allowing them to debate and clarify their understanding. 9. Provide feedback and explanations for each question, ensuring that students grasp the correct concepts. 10. Summarize the key takeaways and address any remaining doubts or questions.

Sample Questions: 1. What does MDP stand for, and what does it represent in the context of decision-making? 2. Define the components of an MDP: states, actions, rewards, transition probabilities. 3. Explain the concept of the Markov property in MDPs. 4. What is the purpose of the reward function in an MDP? 5. Describe the difference between the policy and the value function in MDPs. 6. How does the Bellman equation relate to MDPs? 7. What is the goal of solving an MDP? 8. Explain the concepts of exploration and exploitation in reinforcement learning using MDPs. 9. Describe the difference between on-policy and off-policy learning in MDPs. 10. Provide an example scenario where MDPs can be applied in real-life decision-making.

Note: Adjust the difficulty level and number of questions based on the students’ knowledge and the time available for the activity.